copyright (c) 2001-2021, Karl W Broman https://rqtl.org
The R/qtl package is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License,
version 3, as published by the Free Software Foundation.
This program is distributed in the hope that it will be useful,
but without any warranty; without even the implied warranty of
merchantability or fitness for a particular purpose. See the GNU
General Public License for more details.
A copy of the GNU General Public License, version 3, is available
at https://www.r-project.org/Licenses/GPL-3cim() now includes an addcovar argument for including additional covariates in the model.Revised qtlversion() to handle a case like “1.50”.
Added #define USE_FC_LEN_T in C code that calls Fortran, because of a change in R 3.6.5 that’s going to be required in R 4.2.0.
Fixed bug in addqtl() and addpair() in which the argument forceXcovar wasn’t getting passed to scanqtl().
Fixed bug in stepwiseqtl() regarding the way the null LOD score is calculated.
Added function find_large_intervals() for finding inter-marker intervals in a map with length greater than some value.
Fixed potential problem in documentation, since plot() has moved from the graphics package to base.
Acknowledge R Core Team among contributors, as zeroin function (in C) had been taken from R version 2.15.1. Also add a Copyrights field to the DESCRIPTION file.
Allow rescalemap(), shiftmap(), summaryMap(), and jittermap() to work with plain lists.
Fixed Issue #91 where pull.rf() gives a cryptic error if marker names are not all distinct.
Fix a problem in inferredpartitions() that occurs in the devel version of R.
Small change to read.cross() to avoid warning about length of alleles argument for crosstype="4way". (Fixes Issue #90.)
Small change to read.cross() to avoid messing with X chromosome genotypes when crosstype=4way". (Fixes Issue #88.)
stringsAsFactors will become FALSE rather than TRUE in read.table() and data.frame(), we needed to add stringsAsFactors=TRUE to calls to read.table() and data.frame() in various places. Also there was some ugliness regarding addpair().mqmpermutation() by removing the uses of batches and the batchsize argument.Added plot() and summary() functions for the output of comparegeno().
Added internal functions crosstype() and chrtype().
Added argument crosstype to internal function fitqtlengine() rather than taking it from the cross attributes.
Went through full package to replace use of class(blah)=="blah" with inherits(blah, "blah").
mqmscan() and mqmscanall() now give a warning about omitting the X chromosome, and give a more meaningful error if there are no autosomes.
Improved warning and error messages in several places: rather than “Chromosome misspecified” say “Chromosome __ not found”
Fix bug regarding missing phenotypes in stepwiseqtl().
Fix bug in addpair() re converting map to data frame (getting error like cannot coerce class "A" to data.frame).
Fix bug related to reading 4-way cross data, to ensure that the genetic map for each chromosome is a 2-row matrix.
Fix bug in refineqtl() that gave a warning about min(diff(a)) when there was a single marker on a chromosome. (Issue #78)
Added explanations of a couple of arguments for mqmscan() that had previously not been explained.
Added col argument to geno.image() for custom colors.
Revision to plot.scanone() to handle +/- Inf in the LOD score column.
Add better error message in read.cross with format=“mapqtl”
Revision to summary.map to just give warning if input does not have class “cross” or “map”.
Improved error message in scanone() when phenotypes are not numeric.
Small change in getgenonames() to avoid a problem if there aren’t enough allele codes.
plotLodProfile() now gives a more informative error message if called with a null QTL model.
Revised mqmplot.circle() so that chromosome IDs don’t need to be numbers.
Fix small bugs in c.cross() and checkcovar().
Removed the functions plot.errorlod, plot.geno, plot.info, plot.missing, plot.pheno, plot.pxg, and plot.rf. Changes in the process of submitting packages to CRAN have made this necessary. Each of the packages has alternative names that have been used in the tutorials for some years:
plot.errorlod plotErrorlod
plot.geno plotGeno
plot.info plotInfo
plot.missing plotMissing
plot.pheno plotPheno
plot.pxg plotPXG
plot.rf plotRFIf you have old scripts that use these function names, add the following code at the top:
source("https://rqtl.org/dotfunc.R")Fixed a bug in stepwiseqtl() regarding model=“binary”; a number of cases where I wasn’t passing model to other functions, like refineqtl().
Dealt with possibility NA LOD scores in refineqtl().
Removed questionable use of try() from subset.scanoneperm() and subset.scantwoperm().
Fixed a bug in mqmscanfdr (to permute all chromosomes not just chromosome 1).
Made estimate.map=FALSE the default in read.cross.
Revised read.cross for the “bcsft” cross type so that it should be able to handle sep=“;”.
Removed the file vignettes/fancyheadings.sty
Fixed a couple of minor problems that showed up in byte-compiling the package (breaks outside of loops and use of <<-)
Fixed bugs in formMarkerCovar to give better error messages if markers aren’t found.
Fixed a bug in reviseXdata in case of intercross with both sexes but backward direction only.
Fixed a bug in mqmscan that gave an error about duplicate row names.
Fixed a bug in summary.scantwo for the case of autosome/X chromosome specific permutations.
Fix bugs in pull.argmaxgeno and pull.genoprob for 4-way crosses with include.pos.info=TRUE. (Need to account for map being a matrix.)
Small change to the way Bayesian credible intervals are calculated by bayesint(), concerning the treatment of widths of intervals between positions.
Fix bug in switchAlleles() so that it works with cross type “bcsft” (and will give an appropriate error message for unsupported cross types).
sim.cross gives a warning if model is specified but not used (this is the case for RILs, where we’ve not implemented the simulation of QTL effects)
plot.pxg (aka plotPXG) passes … to plot(), so now you can control the y-axis limits via ylim.
Fixed a problem with column names of output of scantwopermhk.
Fixed a bug in scantwo() when using weights with multiple phenotypes when some of the phenotypes contain missing values. (This is the same as the bug fix in scanone in version 1.38. Reminder of important principle: when you find a bug, look for other possible instances of the same bug.)
Changed the color scheme for plot.scantwo and plot.rf from red/blue rainbow to Viridis (see Option D at https://bids.github.io/colormap/) The plot.rf function has a new argument col.scheme; if you want to use the old red/blue scheme, use col.scheme=“redblue”.
Fixed a bug in cim() that was causing a segmentation fault.
Added a function table2map() for converting a data frame with marker positions (chr, position) into a map object.
Added a bit more detail in the help file for readMWril().
Get rid of everything to do with degrees of freedom in scanone and scantwo. The checks seem to offer little value but rather produce cryptic warnings that confuse many users.
Fixed a bug in scanone() when using weights with multiple phenotypes when some of the phenotypes contain missing values.
In plotLodProfile, if col has length > 1 but no equal to the number of QTL, give a warning, but either repeat or subset the vector rather than just using the first value.
Modified read.cross with format “mm” to handle files with “bc” where we usually see “backcross”.
In read.cross with format=“csv”, “mm”, or “tidy”, don’t let it reorder the chromosomes (which it would do if there were chromosomes named other than numbers < 1000, “X”, or “x”).
drop.markers now gives an error if you try to drop all of the markers.
If cross object contains no genotype data, totmar() and nmar() now give more meaningful errors.
Fixed a bug in scantwo and scantwopermhk in which an error would occur if reduce2grid had been called and assumeCondIndep=FALSE. Now forcing assumeCondIndep=TRUE in this case.
Fixed a bug in plot.pxg, in the case that not all possible genotypes were observed at a marker.
Fixed a bug in stepwiseqtl, where if covar is not a data frame, they don’t get considered in the model.
Fixed a bug in fill.geno for method=“maxmarginal” (wasn’t putting NAs in genotypes with probability < min.prob)
Fixed a bug in refineqtl that arises when multiple QTL are at exactly the same position, which can arise in stepwiseqtl.
Added a function flip.order() for flipping the order of markers on selected chromosomes.
Added scanonevar.meanperm and scanonevar.varperm (from Robert Corty) for permutation tests with scanonevar().
Revised plotPheno (aka plot.pheno) so that one can control the x-axis label and title (also, in a histogram, the breaks).
plotPXG: if infer=FALSE and there are no fully-informative genotypes (e.g., in a 4-way cross), give a more informative error.
geno.image: allow control of x- and y-axis labels; allow suppression of axes.
Removed some warnings about missing end-of-line characters, in read.cross with MapQTL format.
Fixed a bug in scanonevar; was failing with an error about coercing class “A” to a data.frame
Dropped the name summary.scantwo.old(); still available as summaryScantwoOld().
Fix an important bug in summary.cross.
Change a couple of abs() to fabs() in C code.
Added ability to do X-chr-specific permutations in scantwo (argument perm.Xsp, as in scanone). Separate thresholds are obtained for the regions A:A, A:X, and X:X regions, maintaining control of the overall false positive rates.
Added a function scantwopermhk that just performs scantwo permutations with Haley-Knott regression; faster and with lower memory usage than scantwo.
With X-chr-specific scantwo permutations, calc.penalties will give separate main effect for autosome and X chromosome, and separate interaction penalties for A:A, A:X, X:X. For A:A interactions, we still use “light” and “heavy” penalties; for A:X and X:X interactions, only the “heavy” penalty is used. These penalties may be used in stepwiseqtl for better treatment of the X chromosome in automated inference of multi-QTL models.
Added scanonevar() function, for a single-QTL genome scan for QTL affecting not just the mean phenotype but also the variance. (Code from Lars Ronnegard; method in Ronnegard and Valdar Genetics 188:435-447, 2011.)
Added “tidy” format to read.cross and write.cross. This separates the data into three comma-delimited files, for genotypes, phenotypes, and the marker map. Separating the data in this way allows each file to be in a simpler format.
Add another option to fill.geno: impute using maximum marginal probability.
Add function map2table (output like pull.map with as.table=TRUE, but starting with a map rather than with a cross).
Fixed a bug in est_map_ri8self.c (thanks to Rohan Shah)
Fixed a bug in scanone/scantwo stratified permutations in batch, with multiple phenotypes, some with missing values (thanks to John Lovell).
Fixed some bugs in read.cross with format=“mapqtl”.
read.cross with format=“qtlcart” can now read doubled haploids (dh/Ri0).
Fixed potential problem in read.cross with format=“csv” or “csvs” when there are many empty cells in the phenotype data.
Fixed bug in read.cross for format=“csv” that shows up in some rare cases: markers not ordered by linkage group, no positions provided, and chromosome IDs non-numeric. It was a pretty bad bug, as marker genotypes got scrambled.
Fixed some memory leaks in MQM code.
fitqtl with model=“normal” now returns residuals as an attribute.
Added an additional argument to plot.scanone, bgrect, for making the background of the plotting region a different color.
Revised cleanGeno to work with any cross having two possible genotypes (i.e., not just bc but also riself, risib, dh, haploid).
Revised summary.cross so that overall genotype frequencies are given separately for autosomes and the X chromosome.
Fixed typo in a warning in add.threshold.
Fixed a bug in reduce2grid, regarding format of attributes
Fixed a bug in MQM: in some circumstances, the last marker was always included as cofactor; other cleanup in MQM code.
Fixed a problem in write.cross with format=“csv” (for cross types other than BC and F2, it would use incorrect genotype codes if there was no “allele” attribute for the cross).
Add a couple of arguments to plotLodProfile: showallchr, to show all chromosomes (and not just those with QTL), and textsep, to control the separation between the QTL labels and the LOD curves.
Fix a bug in bcsft.c, regarding potentially over-running an array
Fix problem with plotLodProfile when it’s maximized at multiple locations.
Fix problem in refineqtl and stepwiseqtl; map attribute in qtl object would get unintentionally subsetted if the qtl object needed to be re-created.
In addqtl, addint, and addcovarint, have require.fullrank=FALSE be the default; require.fullrank=TRUE remains the default in stepwiseqtl.
Fixed bug in which summary.scantwo was re-ordering the chromosome factor levels.
Fixed problem in formLinkageGroups when used with results of markerlrt(): no recombination fractions so use max.rf=Inf
Added arguments type, cex, pch, and bg to plot.scanone, to be passed to lines() in making the plot. Thus, you can use type=“p” to get points only.
Fixed a bug in scanqtl that showed up if there were missing phenotypes and no covariates.
Slight change to summary.qtl to deal with QTL objects with no QTL.
For the QTLRel package, now “export” reviseXdata() in NAMESPACE.
Added cross type “haploid”. Like backcross (“bc”) or doubled haploids (“dh”) but with genotype labels like “A” and “B” instead of “AA” and “AB”/“BB”.
Added crosstype argument to read.cross, to force a particular cross type (such as “riself”).
For parallel processing, replaced reliance on the snow library with the use of the parallel library.
Added formMarkerCovar(), to facilitate use of markers as covariates in QTL analysis.
Added function addmarker() for adding genotypes for a marker to a cross object.
Added function nqtl() for counting number of QTL in QTL object.
Added examples to help files for plotPXG and effectplot on getting the output.
Slight change to way to handle random number generation for cluster-based computing.
Fix bug in fitqtl-link functions for model=“binary” (re matrix rank)
Fixed write.cross to allow use for BCsFt crosses.
Fixed an out-of-bounds error in the C++ code mqmscan.cpp.
In stepwiseqtl with verbose=FALSE, the initial LOD score is no longer printed.
Improvement in addqtl, addint, scanqtl, stepwiseqtl to better handle collinearity in the design matrix that could give spurious evidence for QTL in large QTL models. This can still be a problem with addpair (and stepwiseqtl with scan.pairs=TRUE).
Slight change to help file for read.cross, to be more explicit about the “csvs” format.
Fixed a bug in read.cross for format=“qtlcart” with RIL data.
Made cross type in “qtlcart” files case insensitive in read.cross. For example, any of Ri1, RI1, rI1, or ri1 will be treated the same.
In plot.rfmatrix, include marker name in title (unless main is provided as an argument).
Add warning message to find.marker if there’s no match for a given chromosome name.
Slight change in find.markerpos(), to speed it up.
Slight change to locateXO to save genotypes to left and right of each crossover.
Small addition to the “A shorter tutorial of R/qtl” (rqtltour2.pdf).
Fixed slight bug in summary.scanone for format=“tabByChr” or format=“tabByCol”.
Fixed bug in fitqtl for case that individuals have missing phenotypes or covariates and there’s a QTL on the X chromosome
Fixed bug in effectplot, regarding coding of genotypes on the X chromosome.
Fixed bug in mqmscan for case when estimate.map=TRUE but plot=FALSE.
Fixed bug in c.cross for case that there are different sets of markers.
Fixed bug in xaxisloc.scanone for case that chromosomes don’t start at 0.
Fixed bug in locateXO; gave core dump if there was just one marker on the chromosome.
Fixed bug in scanone and scantwo for case that weights are used but there are individuals with missing phenotype; the weights weren’t being subsetted appropriately.
Revised example help file for multitrait data to use mqmscanall rather than scanall, since the latter function has no help file.
scanPhyloQTL now gives warning if there are different marker maps.
Fixed bug in mqmaugment; with one phenotype, its name was getting changed to “pheno”.
Revised write.cross to output data in “qtab” format; see https://github.com/qtlHD/qtlHD/blob/master/doc/input/qtab.md
Revised summary.scanone to be more consistent about only picking one row per chromosome even when there are multiple positions sharing the maximum LOD on that chromosome.
Fixed bug in stepwiseqtl; backward deletion steps were not dealing with the drop-one-qtl results from fitqtl appropriately.
Revised fitqtl to include formulas and lod scores as attribute in drop-one-qtl analysis.
Fixed a bug in fitqtl regarding the adjustment for the X chromosome. The problem shows up in stepwiseqtl; if X chr enters model and is then removed, the covariates adjusting for sex and pgm continue to be used. Added argument to refineqtl, fitqtl, scanqtl, addqtl, addpair, to force X-related covariates into model.
In stepwiseqtl, include penalties as attribute in the output.
Slight change to checkcovar(): omit individuals with phenotypes/covariates that are +/- Inf, as well as those that are missing.
Handle missing values in mf.stahl and imf.stahl.
Fixed rare bug in fitqtl regarding X chr loci with interactions.
Fixed bug in sim.cross for type=“bc” that resulted in loss of “X” chromosome type.
Speed up some of the examples in the help file, so that R CMD check doesn’t take so long.
Fixed a major bug in checkcovar, used by scanone and scantwo to omit individuals with missing phenotypes. If there is an “ID” column that is numeric, the wrong individuals could be omitted, and genotypes and phenotypes would be misaligned.
Changed the names of a number of functions, in order to avoid the “Note” in R CMD check, and because Prof. Brian Ripley asked me to.
plot.map -> plotMap
plot.missing -> plotMissing
plot.errorlod -> plotErrorlod
plot.geno -> plotGeno
plot.info -> plotInfo
plot.pheno -> plotPheno
plot.pxg -> plotPXG
plot.rf -> plotRF
summary.map -> summaryMap
summary.scantwo.old -> summaryScantwoOldRevised tutorials to use the new naming scheme.
Revised the emission probabilities for dominant markers in an F2, for the HMM calculations. Previously, we had Pr(O = not A | g = AA) = Pr(O = not B | g = BB) = epsilon/2 these have been changed to Pr(O = not A | g = AA) = Pr(O = not B | g = BB) = epsilon This corresponds to “not A” being “H or B”; similarly for not B. Results will change only for an intercross with dominant markers, and generally only slightly.
Changes to the format of the output of summary.scanPhyloQTL for format=“lod”. The final column is now the maximum LOD score across partitions; the difference between the maximum and the second-highest is now third-to-last; the threshold argument is applied to the overall maximum rather than to that difference.
Revisions to read.cross (for the csv formats) from Steffen Moeller, to give some more informative warnings/errors.
Fixed a bug in scantwo permutations in case that a chromosome has multiple markers but they span < step from calc.genoprob.
Fixed a bug in interpPositions; problems if the input had missing rownames.
Renamed the README.txt file as INSTALL_ME.txt; added a new README.txt that provides a brief description of the package.
Added functions pull.genoprob, pull.argmaxgeno, and pull.draws, to pull out those bits from a cross object as a single big matrix or array.
Added a function inferFounderHap() for crudely inferring founder haplotypes in multi-parent RIL, using groups of adjacent markers.
Added function nullmarkers() for identifying markers with no genotype data.
Revised sim.cross so that founder genotypes are included in output, for 4- and 8-way RIL.
Added HMM functions to handle a special design for MAGIC lines from BioGemma (http://www.biogemma.fr/indexuk.php).
Revised subset.cross and clean.cross so that cross information in 4- and 8-way RIL don’t get lost.
Revised plot.pxg, effectplot and effectscan to give a more informative error if the selected phenotype is not numeric.
Revised qtlversion() to use packageVersion().
Fixed bug in summary.map: class included the function data.frame; not just the character string “data.frame”.
Revised various utility functions to retain the “onlylod” attribute in cross$rf, if it’s there.
Revised plot.map to deal with a pair of maps with markers in different orders (or with some markers appearing in one map and not the other). We still require that the two maps have the same chromosomes and chromosome names (with chromosomes in the same order).
Revised scantwo to allow analysis of individual chromosome pairs, and reorganized the way that scantwo permutations are done (first summarizing each chromosome pair and then overall); this should eliminate the memory problems we’ve had with scantwo permutations.
Added warning to help file for fitqtl() regarding the estimated percent variance explained in the case of linked loci: the values are misleading.
Fixed problem in comparecrosses() regarding Inf/-Inf phenotypes.
Fixed a bug in scantwo, method=“hk”, for multiple phenotypes or permutation tests in batch. This showed up only when there were missing genotypes at one or both putative QTL.
write.cross with format=“csv” now exports genotypes as AA/BB for RIL (previously, genotypes were written as AA/AB).
Fixed bug in addint() and addcovarint()
Revised typingGap to have an argument ‘terminal’; if TRUE, just look at the gap from the terminal markers to the first typed interior marker, giving 0 if the terminal markers are both typed.
Fixed bug in calc.genoprob with stepwidth=“max” in the case that no pseudomarkers are to be added.
Fixed bug in geno.table for the case that X chromosome has just one observed genotype.
No longer allow "" in na.strings in read.cross for csv files.
Revised all calls to data.frame() and as.data.frame() to override global option of stringsAsFactors, so that we know what’s going to happen.
Revised scantwo so that if the ‘chr’ argument is a list, we do just the scans of the chr in the first component against those in the second component.
Slight change in plot.info to deal with inclusion of ‘main’ argument.
Added NAMESPACE file.
Slight changes to avoid some R warning messages.
Slight change to imf.cf to give more accurate results.
Fixed warning message in replacemap.
Fixed warning message in +.scanone.
Fixed bug in mqmfind.marker.
Fixed slight bugs in print.addint and print.addcovarint.
Removed a bunch of unused variables from C code.
Add “addchr” argument to find.pseudomarker. The default is TRUE, and returned non-marker locations have names like “c5.loc25” (as in the output of scanone). If FALSE, that initial “c5.” part is left off, to return just strings like “loc25” (as in the genotype probabilities from calc.genoprob).
Revise calls to rainbow() in plot.rf and plot.scantwo so that they no longer use the ‘gamma’ argument, which is being removed from future versions of R.
Slight change to format of verbose output in est.map with m>0 (that is, under interference).
Enabled est.map to use multiple processors via snow; added argument n.cluster to indicate the number of cluster nodes to use.
Added the option stepwidth=“max” in calc.genoprob, sim.geno, and argmax.geno. This inserts the minimal number of pseudomarkers so that the maximum step between points is as indicated by the “step” argument.
Fixed a bug in refineqtl() that kept it from working for a 4-way cross. (The bug also broke stepwiseqtl().)
Fixed a problem in the internal function dropXcol() that led to a crash in scantwo() for 4-way crosses with an X chromosome.
Fixed a bug in mqmscan() regarding the chromosome names in the output.
Trap cases of X chromosome for crosses other than bc/f2 in stepwiseqtl, makeqtl, addqtl, and addpair.
Added a function phenames() for pulling out the names of the phenotypes.
Small revisions and enhancements to some of the MQM plots.
Revised subset.cross so that if the cross contains QTL genotypes (from sim.cross), these are also subsetted.
Revised replacemap.cross (aka replace.map) so that it will also replace the maps in results from calc.genoprob, sim.geno and argmax.geno, using interpolation if necessary.
Fixed a couple of minor bugs in mqmscan: one giving duplicate row names, another resulting in pseudomarkers outside the terminal markers even when off.end=0.
Fixed bugs in scanone and scantwo regarding batch mode for model != “normal”.
Fixed a bug in refineqtl; it was including all possible covariates refered to in the data frame ‘covar’, even if they weren’t referred to in the formula.
Fixed a bug in plot.geno, introduced in version 1.19, that made it not work with horizontal=FALSE.
Added a tutorial on genetic map construction; find it within the package at docs/geneticmaps.pdf, or (more simply, probably), find it on the web at https://rqtl.org/tutorials/geneticmaps.pdf
Added two additional formats to summary.scanone(), “tabByCol” and “tabByChr”. These produce tables of LOD peaks organized by LOD score column or by chromosome. The tables include approximate confidence intervals for QTL location (as calculated by the lodint() or bayesint() function; which one is indicated by the new argument ci.function). Here’s an example:
bp:
chr pos ci.low ci.high lod pval
c1.loc44.5 1 47.8 35.5 85.0 3.56 0.007
D4Mit164 4 29.5 18.8 30.6 8.09 0.000
sqrt:
chr pos ci.low ci.high lod pval
c1.loc44.5 1 47.8 35.5 84.8 3.63 0.007
D4Mit164 4 29.5 17.2 30.6 8.08 0.000Revised summary.scanoneperm to include a new argument, controlAcrossCol. If TRUE, LOD thresholds will control error rate not just across the genome but also across the LOD score columns.
Added function droponemarker, with the aim of identifying problematic markers by dropping one marker at a time and calculating a LOD score and a change in the estimated genetic length of the respective chromosome.
Added a function pull.rf for pulling out either the estimated recombination fractions or the lod scores, as calculated by est.rf(), from a cross object. Also added a function plot.rfmatrix, for plotting a slice through these.
Added a function cleanGeno for removing genotypes that are possibly in error (as indicated by apparent tight double-crossovers). Use this function with caution.
Added a function typingGap, which calculates, for each individual and each chromosome, the maximum distance between typed markers.
Revised MQMscan so that the output contains covariate information, to be plotted with add.cim.covar().
Revised c.scanone(), c.scanoneperm, c.scantwo, and c.scantwoperm so that the input “…” can be a list of scanone/scanoneperm/scantwo/scantwoperm objects.
Revised plot.geno() so that, for the X chromosome in a backcross or intercross, the genotypes appear appropriately, with females being homozygous or heterozygous and the males hemizygous, though we plot the hemizygous genotypes as if they were homozygotes.
Revised subset.scanoneperm and subset.scantwoperm so that one may pull out a subset of replicates (not just columns). Added functions [.scanoneperm and [.scantwoperm so that one can use [] to subset.
Revised locateXO() so that the output contains a column with the number of typed markers between adjacent crossovers.
In orderMarkers(), if verbose is numeric and > 1, even more information on the progress of the calculations is provided.
Fixed a problem in subset.cross where, in the case that a cross contained numeric IDs, subsetting the individuals resulted in them being sorted according to their IDs.
Added a manual page for the function getid(), which was not previously documented. (It is used internally a great deal, and it may be useful more generally.)
Revised effectplot so that if mname2 or mark2 are given but mname1 and mark1 are not, the arguments get switched.
Fixed a bug in shiftmap().
Added an argument, force, to reviseXdata(), to force a change in the genotypes; this is for use within plot.geno().
Slight change to top.errorlod, so that the output columns are not factors but character strings.
Slight change in plot.geno() so that we use filled circles (pch=23) rather than calling points() twice for each point.
Small changes to mqmplot.circle().
Subtle changes to tutorials new_multiqtl.pdf, new_summary_scanone.pdf, new_summary_scantwo.pdf; added .R files with the code for these tutorials.
Fixed slight bug in getid().
Revised geno.table so that, for 4-way crosses, it gives P-values in most cases. (Previously, it just did so for fully informative markers.)
Changed the default format for max.scanPhyloQTL and summary.scanPhyloQTL from format=“lod” to format=“postprob”.
Added function inferredpartitions for pulling out the inferred partitions for a specified chromosome from the output of scanPhyloQTL.
Fixed a problem in ripple with method=“likelihood”. (The problem arose in revisions in version 1.17.)
Fixed a problem in est.map that resulted in NAs. (The problem arose in revisions in version 1.17.)
Slight changes to “inverse” map functions imf.k, imf.h, imf.cf, so that recombination fractions >= 0.5 return large map distances rather than NAs.
Fixed a bug in summary.scanPhyloQTL so that it works when the input has just one chromosome and so the colnames remain like “AB|CD” rather than getting converted to “AB.CD”.
Implemented the fit of models for binary traits in fitqtl(), by Haley-Knott regression and multiple imputation. This model can also be used in refineqtl, scanqtl, addqtl, addpair, addint, stepwiseqtl, and addcovarint.
Implemented Haley-Knott regression for binary traits in scanone and scantwo.
In mqmscan(), replaced the arguments step.min and step.max with a single argument, off.end (to be more like scanone).
Added functions for the joint analysis of multiple crosses, in order to map QTL to a phylogenetic tree. (A paper describing the methods is in preparation.) The key function is scanPhyloQTL. simPhyloQTL is used to simulate data. plot.scanPhyloQTL, max.scanPhyloQTL, and summary.scanPhyloQTL are the plot, max, and summary functions for the output from scanPhyloQTL.
Added ‘offset’ argument to est.map, which defines the starting position for each chromosome. If missing, we use the starting positions that are currently present in the input cross object.
Added function shiftmap, for shifting the starting points of a genetic map (in a map or cross object).
Added function switchAlleles, for switching the alleles at selected markers in a cross object. (For example, in a backcross, switching AA and AB at a marker; in an intercross, exchanging AA for BB.)
Revised geno.table to have an additional argument, scanone.output. If scanone.output=TRUE, the output is as produced by scanone(), so that one may use plot.scanone() to plot the results.
Added the ability to have ripple() run in parallel, if the snow package is installed. The added argument n.cluster indicates the number of parallel nodes to use. This is reapply only useful with method=“likelihood”; with method=“countxo”, it can be slower than just using one CPU.
Added a function pull.markers, which is the opposite of drop.markers.
Added a function drop.dupmarkers, for dropping markers with duplicate names.
Added an argument ‘bandcol’ in plot.scanone, to specify a color for alternating bands to indicate chromosomes. The default (bandcol=NULL) is to not plot such bands. A good choice might be bandcol=“gray70”.
Added an argument ‘chr’ in est.map, to estimate maps for just a subset of chromosomes.
Revised replace.map (and replacemap.cross) so that the map can have just a subset of the chromosomes in the cross, in which case only the maps for that subset are replaced.
Changed the default in plot.info from method=“both” to method=“entropy”. Also, added an argument “fourwaycross”, so that one can look at the missing information just for the alleles of the first parent (A vs B) or the second parent (C vs D). Finally, added an argument “include.genofreq”; if TRUE, the results will include estimated genotype frequencies at each position.
Added argument ‘simple’ to summary.fitqtl, addint, and addcovarint; if TRUE, output includes neither p-values nor sums of squares.
Added a function allchrsplits(), for testing whether to split a linkage group/chromosome into two, by calculating a LOD score for each interval comparing the full linkage group to the split into two groups at that interval.
Added a function nqrank() for transforming a numeric vector into the corresponding normal quantiles.
Fixed a problem in MQM code regarding negative or really large marker positions.
Fixed a bug in mqmpermutation(), where it was using the wrong phenotype name in the output, if pheno.col is something other than
Revised est.map for 4-way crosses slightly. We’d previously randomized the map before starting EM, which seemed a bad idea.
Fixed a bug in scantwo() for the case that multiple phenotype columns are considered but they have different patterns of missing data. An error occurred due to a number of stupid small mistakes. [Thanks to Ricardo Verdugo for reporting the problem.]
Revised summary.cross so that if markers are at the same location, the warning message indicates which chromosomes are involved.
Revised summary.scanone so that if there is one LOD score column in the output, but the permutation results have more than one, then the first column in the permutation results is used and the others are ignored (and a warning, rather than an error, is issued).
Revised calc.plod() to allow penalties to be infinite.
Revised read.cross with format=“csv” to give an error if the 2nd row has all blanks.
Revised plot.scanoneboot, plot.scanoneperm, and plot.scantwoperm so that they can use the … argument more flexibly. [I use a scheme suggested by Brian Yandell.]
Revised plot.geno so that the … argument can include xlim and ylim.
Fixed bug in convert2sa for case of chromosome with just 1 or 2 markers.
Fixed bug in refineqtl that resulted in sometimes the rownames in the lod profile attribute being messed up.
Revised scanone and scantwo to trap error if perm.strata is not of the correct length.
Added argument ‘ind.noqtl’ to scanone, which indicates individuals that are assigned no QTL effect. This is for rare (largely internal) use for the case that one is combining multiple crosses.
Fix bug in internal function create.map, for case of a sex-specific map with very small length.
Revised fitqtl() so that estimated QTL effects in RIL or doubled haploid are as they should be (half the difference between the two homoyzogotes).
Added a function rescalemap for rescaling a genetic map (as for the case that a cross object has marker positions in basepairs and one wishes to convert them to Mbp or some approximation of cM locations).
Added a warning message to summary.cross for the case that there are chromosomes > 1000 cM in length (which might indicate that they’re really in basepairs).
Revised pull.map to have argument as.table; if as.table=TRUE the map is returned as a simple table with chromosome assignments and positions.
Revised fill.geno to have a third option, method=“no_dbl_XO”, which fills in missing genotypes between markers with exactly the same genotype.
Revised est.map so that the output with verbose=TRUE is less verbose and more informative.
Changes in C++ code, to fix problems that prevented the package from being compiled on Solaris.
Added a function transformPheno for transforming one or more phenotypes in a cross object.
Added a function convert.map for converting a genetic map from one map function to another.
Added functions convert2riself and convert2risib, for converting a cross object to be treated as RIL by selfing or sib mating, respectively.
Added function simulateMissingData, for omitting genotypes at random from a cross object.
Revised write.cross so that it can handle non-numeric phenotypes. Also changed the default for the “digits” argument to NULL, so that phenotypes and map positions are not rounded.
Revised read.cross to have arguments error.prob and map.function, to be used if est.map is called.
Revised locateXO: it no longer shifts the first marker to position 0, and it has a new argument, full.info; if this is TRUE, the output includes not just the estimated crossover locations but also the endpoints of the intervals to which they are known to reside.
Revised summary.cross so that if there are > 30 phenotypes, we don’t show the percent missing phenotypes for all traits but just overall.
Revised stepwiseqtl so that if additive.only=TRUE, you only need to give one penalty.
Revised read.cross with format=“csv” so that initial fields in 2nd row need not be completely empty, but can have white space. (This was a common problem for users importing csv files.)
In plot.qtl, added argument “justdots”, so that one can plot just dots at the QTL rather than arrows and QTL names, and “col”, the color used to indicate the QTL.
Fixed a bug in xaxisloc.scanone for the case of multiple chr/pos in the input.
Fixed an apparent bug in read.cross for format=“qtlcart”; need to treat negative genotype codes as missing.
Fixed a bug in sim.cross for type=“4way”; previously it was just using the female map for both female and male meioses.
Fixed a bug in find.pseudomarkerpos in the case of sex-specific maps (as in a 4-way cross).
lodint and bayesint now stop with an error if chr or qtl.index have length > 1. Before, they gave weird results and a meaningless error.
In read.cross with format=“csv”, give a better error message if there are odd values in the marker positions.
Fixed a bug in scanone/scantwo for RIL on the X chromosome; the X chromosome needs to be treated like to autosomes. We can’t really deal with the sexes properly here.
Revised scanone and scantwo so that, if using multiple CPUs via snow and calculations are stopped early, the cluster nodes are stopped on exit.
Revised summary.cross so that, for cross type “riself”, there’s no warning about a chromosome named “X” having class “A”.
Removed some odd erroneous code from the plot.qtl function.
Fixed a bug in summary.scanone that shows up in the case of multiple LOD columns with permutations and format=“allpeaks”.
Fixed a bug in scanone permutations in the case of multiple phenotypes with missing data.
Fixed a problem in effectplot that arose from an apparent bug in weighted.mean in R version 2.10.1
Revised makeqtl, addtoqtl, dropfromqtl, replaceqtl, and reorderqtl so that qtl objects now include a “chrtype” component, indicating whether QTL are autosomal or for the X chromosome.
Revised scanone and scantwo for multiple phenotypes with missing data so that, with method=“hk” or method=“imp”, the phenotypes are grouped into batches with matching patterns of missing data, rather than just doing each one at a time.
Added a function locateXO (formerly the internal function locate.xo) to estimate the locations of crossovers on a given chromosome.
Added a function, c.scantwo (aka cbind.scantwo), for concatenating multiple scantwo results.
Revised summary.map to deal with the case of a single marker on a chromosome.
Revised scantwo so that phenotype names are in dimnames of the lod component of the output.
Fixed bugs in read.cross with format=“mm” to deal with changes to grep. [replaced grep(“^", …) with grep("^\”, …)]
Fixed a bug in reorderqtl; the n.gen component was not getting fixed.
Fixed a bug in switch.order; results of est.rf were getting messed up.
Fixed some minor issues regarding hyperlinks in help files.
Added the ability to simulate RIL and multiple-strain RIL in the sim.cross function. For the case of multiple-strain RIL, one needs genotype data on the founder strains, which may be simulated with the new function simFounderSnps. The encoding of genotypes in multiple-strain RIL is quite complicated. See the help file for sim.cross.
Added the ability to deal with 4- and 8-way RIL in calc.genoprob, sim.geno, argmax.geno, est.map, ripple, est.rf, tryallpositions, calc.pairprob, and calc.errorlod.
Added a function, readMWril, for reading data on 4- or 8-way RIL.
Fixed a minor problem in read.cross, with format=“csv”, in the case of many phenotypes that resulted in really slow data import. (To read a file with 200 individuals and 1500 phenotypes, it would take about 60 seconds and now takes about 2 seconds.)
Added the ability to have scanone and scantwo permutations run in parallel, if the snow package is installed. The added argument n.cluster indicates the number of parallel nodes to use.
Added a CITATION file; type citation(“qtl”) within R to get information on the citation to use in articles that make use of R/qtl.
You can now subset crosses with brackets, [ ], as with a matrix with rows=chromosomes and columns=individuals. See the examples in the help file for subset.cross.
Added a utility function, findDupMarkers, for identifying groups of markers with identical genotype data. (This is useful for reducing the genotype data in the case of a very high marker density.)
Added a utility function, xaxisloc.scanone, for finding x-axis locations for given genomic positions in a plot of scanone results (useful for adding annotations, such as text or arrows).
Added functions subset.map and [.map for pulling out selected chromosomes from a map object.
The output of tryallpositions, for testing possible positions for a genetic marker, now has class “scanone”, so that one may use plot.scanone, summary.scanone, etc.
Added an argument mark.diagonal to plot.rf(), to include black lines segments around the pixels on the diagonal. This helps to separate the upper left triangle from the lower right triangle. (The default is FALSE.)
In geno.crosstab, the first argument (mname1) can now be a vector with the two marker names; in this case, mname2 should be missing.
Revised clean.scantwo so that, by default, positions must have at least one marker in between them. Added arguments n.mar (no. markers that must separate two positions) and distance (cM distance between two positions). These arguments were also added to scantwo (as clean.nmar and clean.distance).
Revised summary.scanone and summary.scantwo so that the perms argument can contain a single column of permutation results, in which case they are assumed to apply to any LOD score columns.
Revised summary.scanone so that the perms argument can be scantwo permutations results; added an internal utility function, scantwoperm2scanoneperm, for pulling the scanone permutations out of the scantwo permutations.
In plots of output from addpair with a special formula, plot.scantwo now gives just one set of numbers on the color scale.
Fixed a bug in plot.scanone that shows up if the “chr” column is not a factor. Now we convert the column to a factor in advance.
Fixed a bug in stepwiseqtl in the case that the inferred model contains no QTL; deparseQTLformula needs to deal with the NULL case.
Fixed a bug in c.cross regarding “map” attributes in $prob or $draws.
Fixed a bug in cim() [reported by Sandy Taylor] that occurred in the case of multiple marker covariates within a window (and >3 marker covariates on that chromosome.
Fixed a bug in summary.scantwo in case that scanoneX component is numeric(0) and not NULL, which resulted in a major crash.
Revised +.scantwo and -.scantwo so that if the scanoneX component in the input is NULL, the output has scanoneX that is NULL.
Fixed a bug in addpair() in the case that the user gives a formula that includes one but not both of the new QTL.
Revised ripple() to give a warning message if the chr argument is not provided.
In compareorder(), switch.order(), and ripple(), changed the default value for the tol argument to 1e-6 (as in est.map).
Slight change in compareorder() so that the order argument can be of length n.mar+2, but with only the first n.mar items considered.
Slight change in checks of chr argument in ripple and switch.order; added a function testchr for checking that a chromosome argument is okay.
In the output of c.cross, there is a numeric phenotype “cross” that indicates which individuals are from which cross, as a single column.
Revised fixXgeno.f2 so that warnings are given the appropriate allele labels (if they are provided to read.cross).
Fixed a few problems in c.cross regarding the attributes to QTL genotype probabilities and imputated genotypes
Added a function chrnames, for pulling out the chromosome names from a cross.
Revised the software license to the GNU General Public License, version 3.
Minor change in plot.cross so that if one types plot(mycross, mymap) it is shipped to plot.map rather than giving an error message.
Revised the R/qtl tutorial to refer specifically to the GPL v3.
Revised the software license statements throughout the source code (and above), for clarity and consistency.
Revised write.cross so that it may write doubled haploid (type “dh”) data.
Fixed a problem with movemarker regarding the treatment of chromsome names.
Slight change to makeqtl so that QTL names of the form “5@30.0” have ending 0’s left in, if appropriate (so that if one QTL is referred to as “1@12.23”, then another like “5@30” will be given as “5@30.00”, so that all have equal precision.
Added a function find.pseudomarkerpos for finding the position corresponding to a “pseudomarker” name (similar to find.markerpos).
Added an internal function charround() for rounding numbers, turning them into character strings with ending 0’s preserved.
Fixed a slight bug in lodint() regarding the case of multiple positions sharing the maximum LOD score.
In dropfromqtl, addtoqtl, replaceqtl, and reorderqtl, attributes “formula” and “pLOD” are now stripped.
In replaceqtl, changed the argument “indextodrop” to just “index”, as in dropfromqtl.
Added a more clear error message in plot.map in the case that a sex-specific map and a sex-averaged map are input.
In plot.info and plot.geno, we now allow one to use main as an argument for producing a self-defined title.
Slight change in plot.qtl, regarding placement of text and size of arrows.
In summary.fitqtl, print.addint, and print.addcovarint, eliminated an extraneous blank line after the model formula.
Added code from Pjotr Prins enabling R/qtl to be linked against Perl and Ruby, as part of biolib.
Revised the way that the ‘chr’ argument is treated in functions such as scanone, scantwo, etc., to give greater consitency. Numbers are interpreted as character strings to be matched to the chromosome names. Negative numbers and character strings that start with “-” are interpreted as omitting the corresponding chromosomes, matched by name. One may also use a logical vector (TRUE/FALSE), of the same length as there are chromosomes, indicating which chromosomes are to be considered. So if an object has three chromosomes named “1”, “3”, “4”, using chr=2 will result in an error, while chr=3 will give the second chromosome (named “3”).
Also revised the way that the ‘ind’ argument is treated in subset.cross and plot.geno, in the case that the input cross contains individual identifiers in the phenotype data. The ‘ind’ argument can still be a logical vector, but otherwise we first seek to match the values against individual identifiers. For identifiers that are character strings, one may use “-” at the beginning of each to indicate all individuals except those given.
Added an argument ‘batchsize’ to scanone and scantwo, so that in the case that multiple phenotypes (or permutations) are to be run as a batch (with method “hk” or “imp”), they can be run in smaller batches (indicated by batchsize). This can speed things up quite a bit in the case of a very large number of phenotypes (or permutations).
Added two functions for the de novo construction of a genetic map. formLinkageGroups uses pairwise marker linkage information (calculated with est.rf) to partition markers into linkage groups. orderMarkers uses a quick but not very good algorithm for ordering the markers on a chromosome (minimizing the number of obligate crossovers).
Added a function addcovarint, which is similar to addint, but adds one QTL x covariate interaction at a time.
Created functions replacemap.scanone and replacemap.scantwo, which enable one to plot scanone or scantwo results relative to another map (with positions interpolated based on marker locations). These can be used, for example, so that one may plot scanone or scantwo results relative to a physical map.
Added a function replacemap.cross, which is the same as the long extant function replace.map. This was so that I could the functions replacemap.scanone and replacemap.scantwo (see above). All can be used with the ‘generic’ function replacemap.
Revised the functions nchr, nmar, totmar, so that they work for map objects as well as cross objects. Separated the help files for nind, nmar, totmar, nphe, nchr from the summary.cross help file, so that the use of the revised functions can be explained.
Revised the way in which LOD score columns are renamed in c.scanone and cbind.scanoneperm. If labels are given, these are appended to the end of the names, but if labels are not given and there are no repeats in the column names, the column names are left as they were.
Added functions subset.scanoneperm and subset.scantwoperm for pulling out selected LOD columns in the case that permutation tests were run with multiple phenotypes.
Revised calc.penalties so that it can deal with the case of scantwo permutations for multiple phenotypes: Added an argument “lodcolumn” for selecting the phenotype; if missing, penalties for all phenotype are calculated.
Added a function markernames for pulling the marker names out of a cross object (as one long vector).
summary.cross now checks for duplicate chromosome names and chromosome names that start with ‘-’, either of which would cause major problems.
Revised summary.cross so that, if the phenotype data are missing column names, an error is given.
Revised est.map so that the chromosomes are given classes “A” or “X” according to the chromosome types in the input cross object.
Revised geno.crosstab to deal with partially informative genotypes in an intercross or 4-way cross. Added an argument so that (by default) columns and rows with no data will not be printed.
Revised comparegeno to have the option what=“both”, through which the result has the proportion of matches in the lower triangle and the number of matches in the upper triangle. Also, now if what=“proportion” the diagonal has all missing values (rather than all 1’s); otherwise the diagonal contains the number of typed markers for each individual.
Revised movemarker so that one can move a marker onto a totally new chromosome.
Revised sim.cross so that if the input map object has no chromosome names, the chromosomes in the output cross object still have names.
Revised summary.cross to give a warning if the chromosomes are not named.
Added a function convert2sa for converting a sex-specific map object to a sex-averaged map object by pulling out the female marker locations (and issuing a warning if the female and male locations are very different). This is useful for plotting a simpler version of a map estimated for a 4-way cross via est.map with sex.sp=FALSE.
Slight change to countqtlterms(), used by stepwiseqtl(), to skip the parsing of interactions in the case that there are 0 or 1 interactions; this might speed things up slightly.
Fixed a slight with plotModel; the lines indicating interactions were a bit askew.
Slight changes in ripple and bayesint, changing use of rev(order(.)) to order(., decreasing=TRUE)
Added a more clear error message in the case that the number of individuals in the cross doesn’t match the number of individuals in the QTL object in fitqtl, stepwiseqtl, addqtl, addint, addpair, refineqtl.
Fixed a couple of bugs in refineqtl, one concerning convergence and the other concerning dropping individuals with missing covariates or phenotypes in the case that there is just one covariate.
Fixed a slight problem in c.cross: if maps are not precisely the same, we don’t try to combine the genotype probabilities.
Fixed a bug in summary.scanone with format=“allpeaks” for the case that there are no peaks meeting the threshold/alpha.
Fixed a bug in switch.order related to the change in references to chromosomes.
Added a function stepwiseqtl() for performing forward/backward selection to identify a multiple QTL model, with model choice made via a penalized LOD score, with separate penalties on main effects and interactions.
The documents “Brief tour of R/qtl” and “New functions for exploring multiple-QTL models” were revised to discuss the stepwiseqtl function.
calc.penalties() uses permutation results for a 2-dimensional, 2-QTL scan to derive penalties for the penalized LOD scores used by stepwiseqtl().
plotModel() is a new function for creating a simple graphical representation of a QTL model.
Added an additional cross type, “dh”, for doubled haploids. This is treated like a backcross, though genotypes will be indicated as homozygotes. Changed a whole bunch of functions very slightly to accommodate this.
The argument pheno.col in many functions can now be a vector of numeric phenotypes. This could be useful for studying the results with various transformations of a phenotype. The vector has to be numeric, has to have the length equal to the number of individuals in the cross, and has to contain either non-integers or values outside the range 1,2,3,…n.phe. (The revised functions are scanone, scantwo, addqtl, addint, addpair, cim, effectplot, fitqtl, plot.pxg, plot.pheno, refineqtl, scanoneboot, scanqtl, stepwiseqtl.)
lodint and bayesint were revised to accept qtl objects output by refineqtl (with keeplodprofile=TRUE). An additional argument, qtl.index, was added to indicate for which QTL (within such qtl objects) the approximate confidence intervals should be derived. For scanone output, the functions were modified so that, if the results concern just a single chromosome, the chromosome argument is not needed.
In refineqtl, the default for the argument keeplodprofile is now TRUE. The LOD profiles contained in the output of refineqtl are now of class “scanone”.
Covariates (argument covar) in fitqtl, scanqtl, addqtl, addpair, addint, and refineqtl can now be a numeric matrix (with column names), and not just a data.frame.
Permutation results obtained via scantwo now include the maximum LOD score from a single-QTL scan. This is not used in summary.scantwo, but is included for completeness.
Added an argument ‘pvalues’ to summary.fitqtl and addint; if FALSE, the pvalues are not displayed.
Added a function ntyped() which is just like nmissing() except it gives the opposite thing (no. genotypes per individual or marker).
est.rf, for a backcross, had been replacing estimated rec frac > 0.5 with 0.5. This is no longer done.
The print and summary function for QTL objects now will print the formula and penalized LOD (“pLOD”) if they exist as attributes. They also take into account the case of a null QTL model.
Revised makeqtl so that QTL names are of the form “1@15.0” rather than “Chr1@15.0”; the “Chr” seemed gratuitous.
Changed some of the examples in the help files to use pull.pheno in place of references to cross$pheno.
Revised summary.cross so that it pays attention to options(“width”) and prints things more nicely if there are loads and loads of phenotypes or whatever.
We now allow formulas in fitqtl, refineqtl, addqtl, etc., to be character string representations of formulas. (They are then converted.)
Added a function cbind.scanone (which is identical to c.scanone).
The output of fitqtl now includes an element “lod” containing the LOD score from the fit of the full model.
In reorderqtl, if the argument neworder is not provided, the QTL are ordered by chromosome and then by position within a chromosome.
We define a new class, “compactqtl”, for defining the trace through model space in stepwiseqtl() (if called with the argument keeptrace=TRUE). This is similar to the class “qtl” (of QTL objects created by the makeqtl() function), but containing just chromosome IDs and positions of QTL.
Fixed a bug in effectplot in the case that not all possible genotypes are observed in the imputations.
Slight change in plot.scanone so that one may use xlab as an argument. Similarly changed plot.map so that one may use xlab and ylab to change the x- and y-axis labels. Similarly changed plot.scantwo so that one may use xlab and/or ylab to change the x- and y-axis labels. (In plot.scantwo, if just one of xlab or ylab is given, the other is assumed to be the same.)
Slight change to summary.fitqtl and summary.addint so that very long formulas are split across multiple lines.
Slight change to scanqtl to avoid going just outside the defined intervals (specifically, so that refineqtl and plotLodProfile do not go just past the flanking QTL).
Slight change in plot.scantwo to avoid affecting par(“mfrow”) or par(“mar”) in the case zscale=FALSE. Also fixed a slight bug regarding “any(contours)>0” vs “any(contours>0)”.
Slight change in the way refineqtl determines convergence, to try to avoid unnecessary iterations.
Slight change to plot.scanone so that the chr argument can be logical.
Simplied code for ‘cat’ statements in many places; we’d used cat(paste(…)) and the call to paste wasn’t needed.
Fixed an error in scanqtl that arose if there are multiple markers at the same position. Now give a warning message.
The title of the plot produced by plot.rf can now be modified by including the argument ‘main’ in the call.
In plot.geno, if chr is missing, we plot the genotypes for the first chromosome. Changed the label “Position (cM)” to “Location (cM)” (just for consistency across functions).
In geno.crosstab, changed the column and row labels for missing data from “NA” to “-”.
Made a slight change to plot.pxg regarding the locations of the genotype labels on the x-axis.
Revised print.map so that it doesn’t print the log likelihood attribute.
Fixed a bug in addpair if the formula is missing.
Fixed a bug in est.rf for 4-way crosses.
Fixed a bug in c.scanoneperm, c.scanone, and c.scantwoperm regarding the “df” (degrees of freedom) attributes.
Fixed a bug in read.cross with format “csv” (or “csvs” or “csvr” or “csvsr”) so that dec=“,” can be used as an argument.
Fixed a potential bug in read.cross with format “mm” for pulling out the cross type.
Fixed a bug in add.threshold for the case of multiple phenotypes.
Fixed a bug in scanone permutations in the case of a single covariate with some individuals with missing phenotypes and/or covariates.
A more meaningful error message is given in makeqtl in the case that multiple markers are at identical positions, so that qtl locations cannot be determined.
Fixed a bug in read.cross with format=“csvs” or “csvsr” for the case that there are individuals with phenotypes but no genotypes.
Fixed a bug in refineqtl for the case of linked QTL. (Incorrect limits for the search intervals were used.)
Fixed a bug in plotLodProfile for the case of linked QTL. (LOD profiles were not placed correctly.)
Slight change to the internal function reviseqtlnuminformula(), so that the input formula can be a character string.
Fixed slight bug in scanone and scantwo [any(weights)<=0 changed to any(weights<=0)]. Fixed a similar bug in plot.geno [any(errors) changed to any(errors != 0)].
For all functions taking a “pheno.col” argument (including scanone and scantwo), this argument can now be a character string indicating the name of a phenotype. (Previously, it had to be a numeric index indicating the phenotype).
fitqtl now takes a cross object and pheno.col (as with scanone, scantwo and scanqtl), rather than a column of phenotypes.
Implemented Haley-Knott regression for the fit of multiple-QTL models in fitqtl and scanqtl.
Added functions addint, addqtl, and addpair, for exploration of multiple QTL models. addint tries adding all possible pairwise interactions, one at a time, to a multiple QTL model. addqtl scans for an additional QTL to be added to a multiple QTL model. addpair scans for an additional pair of QTL to be added to a multiple QTL model.
Added functions addtoqtl, dropfromqtl, and replaceqtl, for manipulating a qtl object created by makeqtl().
Added a function refineqtl(), for getting the maximum likelihood estimates of QTL positons (as best we can) in the context of a multiple-QTL model. Added a function plotLodProfile which can create a figure with 1-dimensional LOD profiles for each QTL, in the context of a multiple QTL model, as is commonly created for multiple interval mapping.
Added a function, tryallpositions(), for testing all possible positions for a given marker, keeping the order of all other markers fixed.
Added a function, compareorder(), for comparing a given order of markers on a single chromosome to the current one contained within a cross object.
Added some additional marker genotype codes for the phase-known 4-way cross, for a dominant marker with both parents being heterozygous: 11 = not AC, 12 = not BC, 13 = not AD, 14 = not BD.
Revised est.rf, for estimating recombination fractions between all pairs of markers, so that it can give results for many of the incompletely informative markers in a 4-way cross.
Added an additional argument (expandtomarkers) to lodint, bayesint, and summary.scanoneboot. If TRUE, the intervals provided are expanded to the nearest flanking markers.
Added a function geno.crosstab for creating a cross-tabulation of the genotypes at two markers.
Added a function pull.pheno for pulling out the data for a phenotype or phenotypes.
Added a function countXO for counting the number of obligate crossovers for each individual across the genome or on individual chromosomes.
Added a function plot.qtl, for plotting the locations of QTL in a qtl object against the genetic map.
Added a function checkformula for checking the formula in fitqtl/scanqtl, to ensure that it satisfies the hierarchical structure we assume: if a term is involved in an interaction, its main effect should also be included.
Added an additional argument to fitqtl, run.checks. If TRUE, we check the input formula and look for individuals with missing phenotype or covariates. This is included so that the checks are not repeated multiple times when scanqtl calls fitqtl.
Added the ability to calculate joint QTL probabilities assuming conditional independence of QTL genotypes given markers genotypes. (An approximation, but it speeds up scantwo slightly, for a chr versus itself.) Added an argument assumeCondIndep to scantwo().
Added an argument “zmax” to the plot.rf function, for controlling the color scale of LOD scores. Values at zmax are red; values above zmax are thresholded at zmax.
Added functions plot.scanoneperm and plot.scantwoperm for plotting histograms of the permutation results from scanone and scantwo.
Added a function plot.scanoneboot, for plotting a histogram of the results of scanoneboot.
scanoneboot now stops with an error if the argument pheno.col indicates multiple phenotypes.
Revised find.marker to have an argument “index” which may be used in place of the “pos”, to find marker names by their numeric order within a chromosome rather than by map position.
In read.cross, with formats “csvs” or “csvsr”, we now allow that some individuals have phenotypes but no genotypes and vice versa, and the individuals in the genotype and phenotype files are not required to be in the same order.
In the getsex() function, for pulling out sex and pgm for all individuals, we now attempt to infer the status of individuals with missing information. Warnings are given.
Fixed a bug in read.cross.qtx, concerning the case that genotypes are like H:B or A:B, and need to be converted to A:H.
Fixed a bug in effectscan for the X chromosome in the case of an intercross with both directions but just one sex.
Slight change to plot.geno() to make individual IDs shown rather than just numbers, if they are available.
Slight change to effectscan, to pass the “…” argument to the plot function, so that, for example, you can use the ‘main’ argument to put a title on the plot.
Slight changes to top.errorlod() and getid() to deal with a bug for the case that there is an “ID” phenotype column with names like “1_F1”.
Fixed some code in scanqtl regarding dropping individuals with missing phenotypes and/or covariates that really slowed things down. Revised the analogous code in fitqtl.
Added an argument to est.map: omit.uninformative. If TRUE (which is the default, and which was previously the only option), individuals with fewer than two typed markers are omitted. This was added for use by the new function tryallpositions().
Added a function markerloglik, for calculating the log likelihood for a fixed marker. This was added for the use of the new function tryallpositions().
read.cross now prints the cross type at the end.
read.cross (with format=“mm” or one of the “csv” formats) gives a more explicit warning message if phenotypes are to be treated as missing.
Revised summary.qtl to also indicate the number of imputations, in the case that the qtl object contains them.
cim() had previously used a single column for each covariate in an intercross (that is, it assumed additivity of alleles); this is fixed: it now uses two columns. A revised forward selection algorithm for intercrosses was written, to select these pairs of columns together.
Fixed a slight bug in lodint and bayesint that changed the marker names if the LOD peak was at one end of the interval.
subset.scantwo will now drop X chromosome related stuff from the df attribute if the X chromosome has been omitted.
Changed the default tolerance in est.rf and est.map to 10^-6 (rather than 10^-4). Increased the default maxit (maximum no. iterations) to 10000.
Added an extra column in the results of summary.map, giving the maximum distance between markers on each chromosome and overall.
QTL objects produced by makeqtl now include a component “altname”, which will be like “Q1”, “Q2”, … Changed fitqtl to look at this rather than at the column names of qtl$geno.
Made a slight change to plot.scantwo regarding z-limits when zlim is missing and allow.neg=TRUE.
The objects of class “scanoneperm” and “scantwoperm” now have a secondary class (either “matrix” or “list”)
Fixed a bug in scantwo perms for the use of the argument clean.scantwo.
Fixed a bug in summary.cross in the case of invalid genotypes in a cross.
Fixed a slight bug in subset.cross regarding the recombination fractions from est.rf().
Fixed slight bugs in effectplot and reviseXdata regarding the X chromosome in an intercross with both sexes and one cross direction.
Fixed a bug in CIM for the case of multiple marker covariates on the same chromosome.
Fixed a bug in revisecovar() regarding dropping of covariates for the X chromosome.
Fixed a bug in add.threshold.
Fixed a bug in movemarker for the case of sex-specific maps and with the marker being moved to the middle of a chromosome with exactly two markers.
Fixed a bug in geno.table; missing genotypes weren’t shown for the X chromosome.
Fixed a bug in fit.stahl.
Subtle modification to a few of the help pages to conform to a change in R.
Changed the default for plot.geno back to a horizontal plot (horizontal=TRUE); changing it to vertical was a bad idea. Fixed a slight bug regarding F2-type markers in 4-way cross.
In write.cross with the “qtlcart” format, if there is a previous file that would otherwise be overwritten, it is now moved to a file with extension “.bak” rather than “.mov”. Also made some slight revisions to get things in the map file to line up.
Made a minor change to plot.map, so that if the “…” contain xlim or ylim, they are used in place of the defaults.
Completely rewrote the effectscan function, so that it now uses multiple imputation results and deals with the X chromosome appropriately.
Fixed an important bug in fitqtl, in which incorrect results could be obtained if covariates were placed before QTL terms in the formula.
Added an argument “alternate.chrid” to plot.scanone, plot.scantwo, plot.info, plot.missing, geno.image, plot.map, plot.cross, effectscan, plot.errorlod, and plot.rf. If TRUE, the placement of chromosome ID axis labels is alternated, so that they may be more easily distinguished. For plot.cross, alternate.chrid=TRUE has been made the default; for the other functions, FALSE is the default.
In the output from makeqtl, “pos” is now the precise position of the pseudomarkers (rather than just the input values), and the QTL names reflect that (though they are rounded). replaceqtl and addqtl were similarly revised.
In makeqtl, added an argument what=c(“draws”,“prob”); we now pull out either the results of sim.geno or the results of calc.genoprob, and not both. (Only the former is needed at this point; the latter will be used once we have implemented EM/HK/eHK in fitqtl.
plot.geno now works for a 4-way cross; we changed the default to be a vertical plot (ie, horizontal=FALSE).
Added functions print.qtl, summary.qtl, print.summary.qtl, for getting simple information about a QTL object.
Fixed slight bugs in pull.map and replace.map.
Fixed a slight bug in top.errorlod, for the case that there are IDs (e.g., in cross\(pheno\)id) that are not numeric.
Fixed a slight bug in scanqtl.
Changed checks regarding the class of the input to various functions to be a bit more permissive.
Fixed a potential problem (which shouldn’t be realized) in reviseXdata.
Revised the method for calculating genotyping error LOD scores. For each individual and each marker, the error LOD score is calculated assuming that all other genotypes for that individual on that chromosome are correct. The new procedure requires much more computation time (especially in the case of dense markers), but identifies many additional potential errors. A new argument, version, allows one to specify use of the “new” or “old” version of the error LOD score calculations.
Added a function geno.image for plotting an image of the genotype data. This is much like plot.missing, but gives the genotypes in color, rather than just black/white indicating missing/not.
Revised geno.table so that it gives reasonable p-values for the X chromosome and for the case of dominant markers in an intercross. Added a chr argument to obtain results for only selected chromosomes.
Added a function cim() for performing composite interval mapping by one of the schemes used in QTL Cartographer: forward selection at the markers, to a fixed number of markers, followed by interval mapping using those marker as covariates, and dropping any markers within some fixed window around the position under test. The results may be plotted or summarized using the functions for output from scanone(). Also added a function add.cim.covar, for adding dots, to a plot from plot.scanone(), to indicate the selected marker covariates.
Extended the code for fitting the Stahl model for crossover interference to the case of intercross data. (Modified the functions est.map and fitstahl, and the underlying C code.)
Added functions scanoneboot and summary.scanoneboot, for deriving bootstrap confidence intervals for the location of a QTL, but we recommend using lodint or bayesint, instead.
Added a function find.markerpos(), for finding the chromosome and position of a marker (or vector of markers).
Added arguments ‘xlab’, ‘ylab’, and ‘col’ to effectplot(), so that you can override the defaults.
Added a function add.threshold() for adding a significance threshold (estimated via permutation results) to a plot created by plot.scanone().
Revised plot.pxg() so that unobserved genotypes will not be displayed. This was needed for the plot of two-locus genotypes on the X chromosome.
Changed the names in two of the columns in the output from the 2d permutation test, to be “fv1” and “av1” rather than “2v1.int” and “2v1.add”, to correspond more closely to the names in the summary.scantwo output. Also, we now allow the argument “alphas” to be a single number, in which case it is assumed that the same significance level is to be used for all five LOD scores.
Made a slight change in summary.scanone(), so that when p-values are provided, the rownames don’t get lost.
Revised the hyper data set slightly; changed the “alleles” attribute, to be c(“B”,“A”) rather than c(“A”,“B”), as this was a backcross to the B strain.
In scanqtl, if no a fixed model (with no scanning) is fitted, the output is now just the LOD score for that fitted model.
clean.cross was dropping any “alleles” attribute; this is now fixed.
Added a “lodcolumn” argument to lodint() and bayesint().
Fixed a bug in scanqtl; in two-dimensional scans, the first row of the results was wrong.
Fixed a bug in c.cross concerning combining backcross and intercrosses.
Fixed a bug in effectplot() regarding pseudomarkers with names like “c3.loc42.5”.
Fixed a bug in discan, for the case of method=“mr”.
Fixed a bug in write.qtlcart regarding RIL.
Fixed a bug in max.scanone for the case that there is more than one locus with the maximum LOD score. (In that case, we print a random locus, among those having the maximum LOD.)
Revised summary.scanone so that the rule is to pick out LOD scores > (rather than >=) the threshold.
Revised -.scanone, -.scanoneperm so that very small differences get set to 0.
Added ability to halt calculations via Ctrl-c in many of the C routines. (Previously, you’d have to wait for an exit from the C code.)
There was a bug in sim.cross() regarding the QTL effects for a backcross.
Fixed a bug in drop.markers, for a 4-way cross.
Fixed a bug in est.map, for a 4-way cross and the case of sex-averaged maps.
Made a slight change regarding estimating rec fracs in 4-way cross (possibly immaterial).
A slight change in the C code for imf_stahl.
Modified locate.xo() slightly…when there is no crossover, it gives numeric(0) rather than NULL.
Fixed a slight problem with the format of the degrees of freedom in scanone permutation results.
Slight change in the color scheme in effectplot()
Fixed a slight bug in fitstahl() that made it crash if none of m, p, and error.prob were specified. Also revised the function so that we look only for error.prob <= 0.5.
Fixed a slight bug regarding sex-specific maps in the create.map() function.
Slight revision in plot.geno, so that if the “ind” argument contains duplicates of individuals, only the unique individuals are plotted.
Slight revisions to scanone, scantwo, and discan, so that, in the midst of permutations, just one instance of various warnings is printed.
Changed the names of some of the sample data files.
Revised the fitstahl function to use of the estimated map for one value of m as the starting point for the next value. This can really cut down on the required EM iterations and so speeds things up.
In the “map” component of the output from scantwo, the name of the second column is now “pos” rather than “map”, to correspond more closely to the scanone output (and because it is more appropriate).
Fixed a bug in write.cross; in an intercross with all males and all pgm==1, all X chromosome genotypes got converted to AA.
Added a few more verbose error messages in read.cross for the “csvs” format (contributed by Steffen Moller, University of Lubeck).
Fixed a slight bug in scanone with model=“2part” or model=“binary”, that showed up if one first used jittermap().
Added arguments maxit, tol and sex.sp to switch.order()
Fixed a bug in movemarker() for the case of a 4-way cross.
In write.cross.gary(), changed a couple of uses of ‘T’ and ‘F’ to ‘TRUE’ and ‘FALSE’, respectively.
Fixed find.markerpos so that it works with a 4-way cross.
Revised plot.scantwo so that the upper and lower arguments can take values “fv1” and “av1” as aliases for “cond-int” and “cond-add”, respectively.
Fixed a slight bug in scanone for model=“binary”.
Revised write.cross for the “qtlcart” format; there was a problem in the case that there were many markers on a chromosome.
Revised the C code for imf_stahl, to better deal with void pointers.
R/qtl has a new web site: rqtl.org
Revised the format for the output from scantwo. Added a function convert.scantwo for converting from the previous format to the new format. For scantwo results calculated with R/qtl version 1.03 and earlier, you’ll need to use convert.scantwo to convert them to the new format in order to use the summary.scantwo and plot.scantwo functions. (In the previous format, joint and epistasis LOD scores were stored; now we store the joint LOD and the LOD from the additive QTL model. This is so that, if there is a problem with the joint model, it won’t corrupt the results for the additive model.)
Eliminated the ‘run.scanone’ argument from the scantwo() function. scanone is always run. The summaries and permutation tests require these results.
plot.scantwo now has an ‘upper’ as well as a ‘lower’ argument, for complete control over what gets plotted.
Completely revised the summary.scanone and summary.scantwo functions. I have written documents to explain the use of the new functions. These are distributed with the code and are also available at the R/qtl website (https://rqtl.org), under “Tutorials”.
summary.scanone: There is now a format argument, useful for the case that the scanone result contains multiple LOD score columns (for example, for multiple phenotypes). We may focus on a single LOD column (format=“onepheno”), as was done before; include different rows for the peaks in each LOD column (format=“allpheno”); or have one row per chrosome, containing the the position and LOD score for each the peak from each LOD column (format=“allpeaks”). The function now also can take permutation results in order to automatically calculate LOD thresholds or to calculate genome-scan-adjusted p-values.
summary.scantwo: This was quite radically changed. For each pair of chromosomes (including a chromosome with itself), we calculate five LOD scores: the maximum LOD for the full model (2 QTL + interaction), the maximum LOD for the additive model, the difference between these (which concerns a test of whether the two loci interact), and two LOD scores concerning 2 vs 1 QTL: the difference between the full LOD and the best single-QTL LOD for the pair of chromosomes, and the difference between the additive LOD and the best single-QTL LOD for the pair of chromosomes. This is the recommended output, indicated via the argument what=“best”. One may also set the ‘what’ argument to “full”, “add”, or “int”. (See the help file for summary.scantwo.) The ‘thresholds’ argument now requires five values, or one may provide permutation results plus a set of five ‘alphas’ (significance levels). There is also an argument ‘allpairs’; the default is TRUE, in which case all pairs of chromosomes are considered. If allpairs=FALSE, only the self-self chromosomes are considered, so that one may look more easily for cases of possible linked QTL.
summary.scanone and max.scanone now can just just one object, rather than multiple such, as before. However, we have added functions c.scanone and cbind.scanoneperm for combining the columns in multiple runs of scanone (generally either multiple phenotypes or multiple methods).
Completely revised the summary.scantwo function. The old version is saved as the function summary.scantwo.old().
Added an argument perm.strata to scanone and scantwo, to allow stratified permutation tests. If provided, it should be a vector of length the number of individuals in the cross; unique values in perm.strata will specify the strata in which the permutations should be performed. (For example, this could be an indicator of the sexes of the individuals, in which case the individuals will be shuffled separately within males and within females.)
Permutations in scanone can now be done to give separate thresholds for the autosomes and the X chromosome. The argument perm.Xsp is used to indicate that this should be done, in which case many more permutations will be run for the X chromosome than for the autosomes, to ensure similar accuracy. The output of scanone when n.perm>0 is now given class “scanoneperm”, and we’ve written a function summary.scanoneperm for getting LOD thresholds. (This is necessary, since the calculation autosome- and X-chromosome-specific thresholds is a bit complicated.) We’ve also added a function c.scanoneperm for combining the results of multiple permutation runs. (This because their combination is not so simple as before.)
Added functions -.scanoneperm, +.scanoneperm, -.scantwoperm, and +.scantwoperm, for taking sums or differences of permutation results from scanone or scantwo. This is particularly useful for getting LOD thresholds for QTL x covariate interactions, though one must be careful to ensure that the permutations are perfectly linked, which can be achieved with set.seed.
The permutation results from scantwo are completely changed. Rather than keep track of the maximum LOD score for the full model (two QTLs + interaction) and the interaction LOD score, we keep track the genome-wide maxima of the 5 LOD scores calculated in summary.scantwo. (See above.) The output is now given a class scantwoperm, and there is a summary.scantwoperm function for calculating LOD thresholds. There is also a c.scantwoperm function for combining results from multiple runs, largely for the case that multiple sets of permutations were run in parallel.
Removed the ability, in scanone and scantwo, to use the snow package to do parallel analysis on a linux cluster. With the new changes in scanone, I found the code to be too cumbersome.
Added the extended Haley-Knott method (see Feenstra et al., Genetics 173:2269-2282, 2006) to the scanone function. This is faster and more robust than standard interval mapping, and is a better approximation (but slower) than regular Haley-Knott regression.
Revised the sim.cross() function so that, with a backcross, the effect in the “model” argument is to be specified as the difference between the average phenotypes for the heterozygotes and the homozygotes. (Previously, it was 1/2 this, which is different from the typical parameterization.)
Added the ability, for a backcross, to estimate a genetic map under the Stahl model for crossover interference (of which the chi-square model is a special case). Also added a function, fitstahl, for getting the maximum likelihood estimates in the Stahl model (or the chi-square model); the genotyping error probability may be treated as known or may also be estimated.
Added an argument, “use”, to scanone and scantwo, for indicating, in the case that multiple phenotypes are to be run, whether only individuals with complete data on all phenotypes (use=“complete.obs”) or all individuals (use=“all.obs”) are to be used.
The degrees of freedom are added as attributes in the output from scanone and scantwo, including the case of permutations.
In read.cross, the symbol “#” is no longer treated as a comment character by default. The default is to use comment.char=""; that is, no symbol is treated as an indicator of comments. For the comma-delimited file formats, one may have a character interpreted as indicating comments using the comment.char argument.
Fixed a bug for the new “batch mode” permutations in scanone and scantwo with method=“hk” or =“imp”. The trick only works if there is no X chromosome or all individuals have the same sex and cross direction or permutations are done stratified within sex and direction.
Added an argument “show.marker.names” to plot.map and plot.scanone, so that marker names can be added to these plots.
write.cross can now write data in the “csvr”, “csvs” and “csvsr” formats.
Added a function plot.pheno for plotting a histogram or barplot of a phenotype distribution.
Added a function condense.scantwo for producing condensed versions of scantwo output, containing just the maximum LOD scores on each pair of chromosomes. One can get summaries from these but not plots.
In plot.info, added step, off.end, error.prob and map.function arguments. The function now always calls calc.genoprob rather than relying on the values in the data.
Changed the default cutoff for genotyping error LOD scores in top.errorlod and plot.geno to 4.
Changed the name of the function clean() to clean.cross() and made a new function clean() that will dispactch a cross object to clean.cross. Added a function clean.scantwo() for cleaning up the output of scantwo: any values that are missing or are < 0 are replaced by 0 and any LOD scores for pairs of loci that do not have a marker between them are set to 0.
The output of scantwo() now contains the original genetic map as an attribute; this is needed for clean.scantwo().
Slightly revised effectplot() so that if sim.geno hasn’t been run, it is run (with a single imputation) before the plot is created. I also changed the names in the output, so that it is “Means” and “SEs”. Changed the examples in the help file for effectplot.
Added an argument “lodcolumn” to max.scanone, so that it behaves like summary.scanone.
Added a function subset.scanone() for pulling out particular chromosomes or LOD score columns from scanone output.
Added a function find.pseudomarker() for identifying the name of a pseudomarker that is closest to a specified position. This is useful for the effectplot() function.
In scanone and scantwo, there is now a warning printed when individuals with missing phenotype are dropped. Also, a slightly better error message is printed if addcovar or intcovar are not numeric. Also added a warning message if addcovar or intcovar appear to be over-specified (having columns that need to be dropped).
Fixed a slight problem in the column names from scanone() in the case of multiple phenotypes; changed the convention for this. Now the columns will just have the phenotype names.
Fixed the help file for read.cross concerning the individual identifiers and about which files are used for the csvs and csvsr formats.
Revised nmissing() so that if what=“ind” and individual IDs are included as a cross phenotype (named “id” or “ID”), these are used as names in the output.
Revised summary.cross() to include a check of whether the individual IDs (in a phenotype named “id” or “ID”) are unique. If they are not, a warning is issued.
Changed the “pheno” argument in plot.cross to “pheno.col”, to be more consistent with other functions.
Changed the name of the argument “which” in plot.rf and nmissing to “what”.
Added an argument “verbose” to the ripple function; if verbose=FALSE, the function doesn’t print anything. Also modified print.summary.ripple so that it prints no more than 6 rows.
Revised plot.missing so that if reorder=TRUE, the reordering of individuals is done by the average of only the numeric phenotypes (rather than all phenotypes, which gave an error).
Fixed a slight bug in summary.cross() regarding duplicate marker names.
Fixed a bug in scanone() that messed up the X chromosome label in the case of method=“imp” with multiple phenotypes.
Fixed a bug in scanone() regarding method=“mr-imp” with permutations.
Revised the listeria data set slightly; added an “alleles” attribute, with alleles “C” and “B”, as this was a cross between BALB/cByJ and C57BL/6ByJ, and those strains were coded C and B in the original paper. This takes advantage of a feature added in version 1.03. Also added a phenotype “sex” that indicates all individuals are female.
Added a phenotype “sex” in the hyper data, indicating that all individuals are male.
Modified checkAlleles() so that it doesn’t give an error if one inputs data for only the X chromosome.
Revised calc.errorlod() so that it won’t give a warning if it has to run calc.genoprob() because such probabilities aren’t available. It will still give a warning if it has to re-run calc.genoprob() with a new error.prob value.
Slight revision of plot.scanone() to include “Chromosome” as an x-axis label if multiple chromosomes are plotted.
Fixed a slight bug in plot.info for the case that results are only at the marker positions.
Changed the name of the “cols” argument in plot.pxg to “col”. (This argument was added in version 1.03.)
Revised summary.cross so that if the “jittermap” warning is printed, it’s only printed once.
Made a slight change to summary.map and print.summary.map, so that “sexsp” is an attribute.
A couple of changes were made to the write.cross.qtlcart(): round the map locations, make sure backcross code is correct, and make sure RIL data is written as 0/2 rather than 0/1.
Revised plot.info() so that if method=“entropy” or method=“variance”, only the column requested is returned. (Previously, the other was also given, but with all 0’s.)
Fixed a bug in sim.cross for type=“4way”; it would stop with an error if QTLs were to be simulated.
Fixed a bug in fill.geno for the case that a chromosome has just one marker.
Removed the function convert.cross(), which converted cross data from the format used in R/qtl version < 0.65 to the current format. This shouldn’t be needed anymore.
Fixed a bug in plot.pxg; the plot was messed up one requested an autosomal marker and an X chromosome marker, but with the X chromosome marker listed first.
Fixed subset.cross() so that the attribitutes in the results of calc.genoprob, calc.errorlod, sim.geno, and argmax.geno, don’t get lost on subsetting. This was important to ensure that the package will conform to a change that will occur in the next release of R.
Added a function checkAlleles() for identifying loci that might have their alleles switched (in an intercross, if AA and BB are switched, or in a backcross if AA and AB are switched). The X chromosome is ignored. An internal function, checkrf() was removed; this was previously called by est.rf() but wasn’t well written.
Added an argument, alleles, for read.cross(), which takes two single-character allele labels that are included as an attribute in the cross and will be used as labels throughout the program (for example, in geno.table, effectplot and plot.pxg). This required numerous small changes throughout the package.
The maps used for the results from argmax.geno(), calc.genoprob() and sim.geno() are now saved as an attribute on the data they create (within the cross object) so that create.map() doesn’t have to be called repeatedly.
Moved the code for simulating genotype data in sim.cross() into C, to increase speed, and modified it so that one may simulate under Frank Stahl’s interference model (which includes the chi-square model as a special case).
If one includes a phenotype named “id” or “ID”, this will be used in top.errorlod(), plot.errorlod(), and plot.geno() as identifiers for the individual.
Added a warning in summary.cross() if there are multiple X chromosomes; the summary now includes the names of the autosomes and X chromosome (for diagnostic purposes).
Revised plot.rf() so that, if the results of est.rf aren’t available, that function is run.
Made a slight modification to the bayesint() function for getting Bayes credible intervals from scanone() results.
Added a “chr” argument to pull.geno() and pull.map(), so that you can pull out the genotype data or map for a selected set of chromosomes.
Fixed a slight bug in locatemarker(), used by makeqtl().
Added a function print.map() so that when you print a map, all of the class stuff doesn’t get in the way.
Included an additional argument [stepwidth = c(“fixed”, “variable”)] in the internal create.map function, for Brian Yandell and the R/bmqtl package. This argument was also added to calc.genoprob(), sim.geno() and argmax.geno(). We also added a “stepwidth” attribute to the bits that these functions produce.
Added an argument, “lodcolumn”, to the function max.scantwo, for picking out a single phenotype in the case that the results concern multiple phenotypes. As with summary.scantwo() and plot.scantwo(), this function will only give the results for a single phenotype.
Made a slight change regarding the sizes of the labels in plot.pxg() and added an argument concerning colors.
Fixed a bug in scanqtl() regarding the X chromosome.
Revised plot.map() slightly so that one can use “main” as an argument, to create a custom title (such as "").
Fixed a bug in sim.map() regarding sex.sp=TRUE
Modified scanone() and scantwo() so that they may analyze multiple phenotypes simultaneously. This can greatly speed up the analyses with Haley-Knott regression (method=“hk”) and imputation (method=“imp”). We can use this trick to speed up permutation tests: create multiple permuted phenotypes and then analyze them all at once.
scanone() results no longer include parameter estimates (such as the phenotypic averages for each genotype group and the residual SD). The bookkeeping for this became too painful as we moved to allow multiple phenotypes to be analyzed simultaneously. To get such estimates, use fitqtl(). fitqtl() currently works only via the imputation method, but we expect to soon implement multiple interval mapping (MIM) and also Haley-Knott regression.
scantwo() with method=“em” now works for the X chromosome, including with model=“binary”.
Modified the “map10” dataset: a genetic map modeled after the mouse, with markers having an approximately 10 cM spacing. We’ve revised the chromosome lengths to match those in the Mouse Genome Database.
Dropped support for intercrosses with sex-specific maps (class “f2ss”).
Changed the meaning of the argument “lodcolumn” in scanone(). It now should be an index starting at 1 rather than 3. I think this will be more clear for the case of LOD scores from multiple phenotypes, though perhaps it will be less clear.
summary.scanone() now takes an argument “lodcolumn”; if a single scanone output is given as input, it picks off peaks using those LOD scores. (As with plot.scanone, this is indexed starting at 1.)
Similarly, added a “lodcolumn” argument to plot.scantwo() and summary.scantwo(), for the case that the scantwo results are for multiple phenotypes; only results for a single phenotype are used by these functions, and “lodcolumn” indicates which one.
Modified summary.cross() to give a warning if there are markers at precisely the same position. Added a function jittermap() to assist in fixing this. Numerous functions run into problems if there are markers on top of each other. Revised the hyper dataset so that it doesn’t have this problem.
Switched the order of the arguments “model” and “method” in scantwo() to match that for scanone().
Fixed a slight bug in max.scanone() that led to an unnecessary warning message.
Fixed a slight bug in locate.xo(), used by plot.geno() to identify the locations of crossovers.
Made a slight revision to read.map.qtlcart(), so that chromosome names are not required in the map file, and so that more informative messages are displayed if marker or chromosome names are not found.
Modified qtlversion(), which prints the installed version of the package, to use library(help=qtl) rather than installed.packages(). This is a lot faster.
Added, to summary.cross(), a check on whether multiple phenotypes have the same name.
Modified plot.cross() so that it will work if multiple phenotypes have the same name (though that shouldn’t happen).
Fixed a bug in fitqtl() regarding the names of coefficients for interactions between QTLs and covariates when get.ests=TRUE.
Fixed a slight problem in read.cross.csv() and read.cross.csvs() so they will read in 4-way cross data. You need to use genotypes=NULL.
Modified c.cross() so that it can combined crosses typed at different numbers of markers. The number of chromosomes must be the same, and the genetic maps must be consistent.
Modified plot.scanone() so that you can give it a “ylab” argument to override the y-axis labels. Eliminated the “main” argument, as that can be passed via “…”.
Modified the threshold for est.rf() to print warnings about possibly switched genotype data.
Fixed a slight typo in the help file for plot.scantwo().
Fixed a bug in calc.pairprob() (used by scantwo) for RILs.
Fixed a slight bug in scanone() for permutations; it dropped covariates in permutation tests with model=“binary”.
Fixed a slight bug in read.cross with format “csvs”, for the case that the argument genotypes=NULL.
Fixed a slight bug in checkcovar() used by scanone() that arose when there were missing values in the phenotype data.
Added a utility function chrlen() for pulling out the lengths of all of the chromosomes.
Revised read.cross to include three additional data formats:
"csvr" The format "csv", but with rows and columns
interchanged. I call that a "rotated" version of the CSV
format, but it's really a transposed version.
"csvs" The format "csv", but with separate files for the
genotype and phenotype data. Note that the first column
in the phenotype data should specify the individuals'
IDs, and that there should be a column in the phenotype
data with precisely the same name, and the individuals
should be in precisely the same order.
"csvsr" The format "csvs", but with the genotype and phenotype
files rotated (really transposed).Added example files (of the listeria data) in these formats in the “sampledata” directory.
plot.scantwo can now plot the additive LOD scores in the lower triangle (with the argument lower=“add”)
Fixed a bug regarding the X chromosome in scanone() with the use of covariates.
Modifying plot.geno() to put X’s at inferred crossover locations.
Modified plot.rf() so that the lines between chromosomes are white.
Added a “chr” argument to plot.map, so that a selected set of chromosomes may be plotted.
Changed the default value for the error.prob argument from 0 to 0.0001 in est.map(), calc.genoprob(), sim.geno(), and other functions.
Revised fitqtl() so that it can provide estimated QTL effects (using the imputation method), though this is working completely only for autosomes in backcrosses and intercrosses at this point.
Revised fitqtl() so that it treats the X chromosome appropriately.
Fixed a bug in read.cross for the “qtlcart” format. There was a problem in the reading of map files if the inter-marker distances were at all out of alignment (which occurred when two markers were 100 cM apart).
est.rf() was revised to treat the X chromosome properly in an intercross.
Fixed a bug in scanqtl() in the case that covar=NULL was specified; this should be treated just like if it were missing.
Modified plot.scantwo() so that the default is lower=“joint”; I’ve become suspicious of lower=“cond-int” and “cond-add”.
Added another argument to plot.scantwo(): point.at.max, for plotting an X at the maximum LOD.
Added an argument, “verbose”, to scanqtl(), to give feedback about progress.
Revised scanqtl() so that makeqtl() doesn’t get called repeatedly, but rather the imputations get copied over. This sped the thing up immensely.
Replaced calls to print.matrix() in print.summary.ripple(), as the function will be dropped from R ver 2.2.
Fixed a bug in plot.pxg(): it halted with an error in the case of multiple markers on the same chromosome.
Fixed a bug in fitqtl() that made it die with only one QTL.
plot.scantwo() now gives cM locations on the axes in the case of just one chromosome.
Fixed a bug in find.marker.
Fixed a slight bug in plot.scanone()
Added a function qtlversion() to print the version number of the currently installed version of the package.
Fixed a bug in plot.scantwo() regarding the X chromosome in the case that markers were included in scan but are not to be plotted.
Fixed a bug in scanone() and scantwo() regarding the use of sex and/or pgm as covariates on the X chromosome; this affected only results with method=“imp” and only for the X chromosome.
Revised some of the help files so that they conform to the rules for the latest version of R.
Revised scantwo() by imputation so that the interaction LOD score is obtained by combining across imputations for each of the full and additive model and then subtracting, rather than subtracting and then combining.
Fixed some typos in the help files.
scanone() now allows additive and interactive covariates in the case model=“binary” (that is, for a binary trait). This uses a logit link.
scantwo() now allows analysis of binary traits (model=“binary”), for method=“em” only.
Added a few new utility functions: bayesint() for calculating Bayesian probability intervals [cf lodint()], comparegeno for comparing individuals’ genotypes, and strip.partials() for removing partially informative genotypes.
Added +.scanone() and -.scanone() for adding and subtracting the output of scanone()
Revised summary.scanone() and print.summary.scanone() so that it can summarize the result of multiple scanone() results together.
Added code (the function sim.cc) for simulating the “Collaborative Cross” (8-way RILs) and for calculating QTL genotype probabilities and identifying the most likely genotypes (using Viterbi) with SNP data on such lines.
Revised plot.scanone() so that when one chromosome is plotted, it starts whereever the first marker on the chromosome was placed, and not necessarily at 0.
Revised plot.map() so that shifting chromosomes so that the first marker is at 0 cM is optional. (Use shift=FALSE to not do such a shift.)
Fixed the issue regarding use of sex and/or pgm as covariates for the X chromosome; such covariates are dropped just for the X chromosome.
Revised plot.pxg() so that it no longer returns Rsq, fit and so forth. I’ve gone back to returning just information about the data that are plotted. I added an argument “main” in the case one wishes to use a plot title different from the default.
Changed the default for plot.geno from horizontal=FALSE to horizontal=TRUE.
switch.order() no longer resets the location of the first marker on the chromosome to 0 cM, but retains the offset from the original map.
Changed “trace” as an argument to “verbose”, to avoid clashes with the built-in R function trace()
Revised summary.cross() to check the class of chromosomes (the components in cross$geno); they should each have class “A” or “X”.
Revised subset.cross() so that it won’t produce duplicate chromosomes, and to treat missing values in the ind argument.
Fixed a slight bug in fitqtl() regarding the drop one analysis when there is just one QTL.
There was a slight bug in plot.pxg() regarding the X chromosome.
Fixed a bug in scanone() regarding the X chromosome for RILs.
Fixed a slight, silly bug in est.map() for sex-specific maps, in which the location of the initial marker was randomized.
Revised plot.scanone(), plot.scantwo(), and other plotting functions so that they don’t show their NULL return values.
Fixed a bug in makeqtl() regarding the X chromosome if there are genotype probabilities.
Revised the internal checkcovar() function to check that the chosen phenotype for scanone(), scantwo(), etc., is numeric. Previously, an rather uninformative error message was given.
Modified the convergence criterion for scantwo() by the EM algorithm; we now just look at the log likelihood, and not at the parameters.
Fixed a bug in read.map.qtlcart().
Fixed bugs in scanone and scantwo for method=“imp”, for the case that one has exactly one imputation. Fixed a memory-overwrite problem in scanone() with method=“imp”.
Fixed a bug in fixXgeno.f2; a slight error that shows up in the case the pgm values are switched.
Added code to simulate Collaborative Cross data and to do calc.genoprob() and argmax.geno() on such data, though none of this is documented yet.
movemarker() now updates the results of est.rf, calc.genoprob, calc.errorlod, sim.geno, argmax.geno, if they are available. (est.rf is simply re-run; the others are re-run for just the relevant chromosomes).
calc.errorlod had neglected to include the map function as an attribute. This is now fixed.
Revised scantwo with method=“em” so that it prints the verbose warning messages only if the verbose argument is > 1. With verbose=TRUE, only the chromosomes are printed.
There is no longer an argument “sep” for the function read.cross. Instead, we use “…”, which is passed to the function read.table (all this just for the “csv” format). (sep=“,” is still assumed for that format). This change allows one to use sep=“;” and dec=“,” which many people prefer.
The function read.cross now automatically converts X chromosome genotype data into the standard internal format (with all individuals coded like an autosome in a backcross).
The functions scanone() and scantwo() were revised so that they treat the X chromosome appropriately. The argument “x.treatment” has been deleted. What had been x.treatment=“full” (namely, that hemizygous genotypes are considered different from homozygous genotypes) is now forced. The big change concerns the “null hypothesis” for the X chromosome, which includes sex and/or “pgm” as covariates, in order to avoid spurious linkage on the X due to sex differences in the phenotype. See the help files for these functions for details. Note that the output of the scantwo function has changed somewhat; it would be best to re-run scantwo with this new version of the software.
Added a function movemarker() for moving a marker from one chromosome to another.
Revised scanone(), scantwo(), discan(), vbscan() and plot.info() so that inter-marker positions are cited as “c.loc” rather than “loc.c” or "loc*". Added a function convert.scanone() for converting scanone output to the new format. (The new plot.scantwo will interpret, for the old version of scanone output, every inter-marker position as a marker.)
Added a function find.pheno() [from Brian Yandell] for finding the phenotype column with a particular name.
Added a function find.flanking() [from Brian Yandell], which is similar to find.marker(), but gives not just the closest marker but also the left- and right-flanking markers.
Added a function print.cross() which prints a short message and then calls summary.cross(). This was added in order to avoid the essentially always unintentional printing of an entire (generally quite large) cross object.
Modified summary.scantwo to allow a type option to get summaries based on peak “joint” or “inter” and to allow negative thresholds relative to max joint, inter, or individual LODs [from Brian Yandell; I’m not really sure what this means].
Modified plot.scantwo to modify the contour option, making 1.5 from the peak the default on each half-image, and to take a numeric vector of drops from the peaks. Added arguments col.scheme and gamma for different color schemes [from Brian Yandell].
Hugely sped up plot.scantwo for the case of lower=“cond-int” and lower=“cond-add”! (By hugely, I mean by a factor of 50 or more.)
Added a function summary.map() for giving summary information about a genetic map.
In read.cross, if chromosome names start with “chr” or “chromosome” (ignoring case) these initial strings are removed.
est.rf now returns a warning if a marker appears to have its genotypes miscoded (so that it shows a rec. frac. > 0.5 with LOD > 3).
Deleted the function pull.chr(), which was deprecated in version 0.89 in Nov, 2001. You can use subset.cross() instead.
Fixed a bug in calc.errorlod regarding the X chromosome in an intercross.
read.cross with format=“qtlcart” printed on screen the number of individuals but called it the number of phenotypes. Brian Yandell provided another revision to this, to fix bugs regarding phenotypes that are factors.
Fixed a slight bug in summary.cross() in the case that a cross contains no autosomal data.
Fixed a bug in read.cross for the mapmaker format; if a marker or phenotype name were listed without any data, an error resulted.
Fixed a bug in summary.scanone which resulted in multiple rows being returned for a single chromosome if multiple positions shared the same maximal LOD score.
Fixed bugs in plot.scanone and plot.scantwo for the case that the “chr” argument was used with chromosomes not in the usual order.
read.cross with format=“csv” now prints a warning if unusual entries are seen in the genotype data.
Revised the geno.table() function so that its first column is the chromosome number
Modified read.cross.qtx(); “X” or “x” in a phenotype is a missing value.
Changed a call to print.coefmat() to a call to printCoefmat(), as the former is being discarded in favor of the latter.
Changed the name of the utility function fixXdata() to reviseXdata(). This function deals with the X chromosome genotypes in scanone() and scantwo().
Modified the source code in hmm_bc.c, hmm_f2.c, hmm_main.h so that we don’t repeatedly calculate log(0.5), log(2.0) and log(0.25), but rather rely on #define statements
Got rid of the WIN32 stuff in addlog and subtractlog in util.c, which were used in version 0.97 as I’d not been able to get log1p to work.
plot.missing now gives a more meaningful error if the argument “reorder” is greater than the number of phenotypes.
I split up the read.cross.R file into several smaller files, for more easy revisions.
Revised the function comparecrosses(), adding an argument “tol” so that the genetic maps and phenotypes do not need to be exactly the same, but can be identical to within the specified tolerance, “tol”. Also, a warning (rather than an error) is produced if the inter-marker distances are the same but the position of the initial marker is different.
Fixed a slight bug in write.cross for the case of phenotypes that are factors.
Fixed a problem in read.cross for format “gary”; now I pass the “na.strings” argument for reading the phenotype data.
Fixed a problem in read.cross with format “gary” or “csv” for ensuring that phenotypes that appear to be numeric are read as numeric and not as factors.
Modified the function getsex(), which finds and interprets the sex and pgm columns in the phenotype data, for the case where sex is read as a factor with just one level (either “F”, “f”, “M”, or “m”).
Added more understandable warning/error messages to plot.scanone if a chromosome ID in the “chr” argument doesn’t match those in the scanone output.
Fixed a problem in the example data “badorder”; chromosomes 2 and 3 were switched.
Fixed a bug in read.cross for the QTL Cartographer format for the case that there is just one individual.
Modified some of the C calls to FORTRAN subroutines, using the macro F77_CALL(), as this is recommended in the R documentation. (Fortran routines currently used: dqrls, dpoco, dposl)
Modified est.map so that it removes individuals with fewer than two typed markers. Their presence is of no value in estimating the map, and can really slow things down.
Revised a number of the help files to make the automated tests of the integrity of the software much faster.
Revised read.cross.mm() so that (a) the cross type is taken as the 4th word (rather than the last word) on the first line, in case someone includes additional characters, and (b) if the sample map format is used but chromosome assignments are not provided, a meaningful error message is displayed.
Made a few very minor revisions to the “rqtltour.pdf” tutorial.
Revised getgenonames() and reviseXdata() to remove the x.treatment argument, which is now assumed to be “full”. Revised effectplot() and plot.pxg() accordingly.
Modified the utility function to do map expansion in RIs for the X chromosome. Need to modify things further to take account of the lack of balance on the X chromosome…it’s quite different from a backcross.
Revised plot.pxg() so that it can take a vector of marker names [from Brian Yandell].
Revised plot.scantwo to allow different color schemes and to give contours at 1.5 (or other specified values) below the maximum LOD [from Brian Yandell].
Revised summary.scanone and print.summary.scanone so that summary.scanone will never print anything, but will leave it to print.summary.scanone to do so. (Previously, summary.scanone printed a message if there were no peaks above the LOD threshold.) summary.scantwo and print.summary.scantwo were revised similarly.
Modified plot.scanone to allow NAs in the LOD scores.
Revised scanone and scantwo so that n.perm=0 is treated the same as if it were not provided.
Fixed a bug in plot.rf() in the case that chromosomes are provided out of order, in which case the thing plotted garbage. The fix involved revising subset.cross() so that the chr argument is sorted.
Replaced the example data sets with compressed versions.
Had to modify part of the C code for scanone with model=“2part”. I’d hard-coded some of the array limits!
Changed the default line types and colors in plot.scanone().
Added a warning for scanone() and scantwo() about the number of individuals that are omitted due to missing phenotype or covariate information.
Revised write.cross so that X chromosome data is converted back from our internal format to the standard format.
Added an argument “weights” to the functions scanone and scantwo, to allow differential weighting of individuals in a genome scan; these are only used with model=“normal”.
Modified the function “plot.scantwo” for plotting the results from a two-dimensional, two-QTL genome scan. There are two new arguments: lower controls what LOD scores are plot in the lower triangle (lower=“joint” corresponds to the previous version of this function), while nodiag controls whether to plot the scanone results on the diagonal. Using lower=“cond-int” (the default) gets rid of the “coattail” effect often seen when plotting the joint LOD scores. Ted Lystig for suggested this modification.
Added a new function effectscan() for plotting the estimated allelic affect at all markers on selected chromosomes.
Modified write.cross so that it will output data in “gary” format.
Added a function lodint, for calculating LOD support intervals based on results from scanone.
Added a function nmissing(), which calculates the total number of missing genotypes for each individual in a cross, or for each marker.
Added a function pull.geno() for pulling out the set of genotype data for a cross as a single big matrix.
Added a function comparecrosses() for verifying that two objects of class “cross” are identical.
The results of geno.table() now includes P-values from chi-square tests for Mendelian segregation.
Modified the function c.cross for combining crosses. You can now combine backcrosses and intercrosses, provided that they have exactly the same genetic maps. Further, we no longer discard the results of sim.geno and calc.genoprob, provided that the same step, off.end, and error.prob arguments were used.
Added an additional argument, cex, to the function plot.geno, for control of the size of the points in the plot. Also changed the orientation of the plot when horiz=FALSE, so that the centromere is at the top of the figure rather than the bottom.
Fixed calc.pairprob so that it will work for RI lines (“risib” or “riself”). Thus, scantwo should work with RI lines now.
Updated read.cross for format=“gary” so that the marker positions file (“mapfile”) and phenotype names file (“pnamesfile”) are not necessary. Set these arguments to NULL (e.g., mapfile=NULL) if the corresponding files are not available.
Added a “chr” argument to max.scanone, so you can get the maximum LOD score for a particular chromosome.
Revised the function switch.order() so that, if estimated recombination fractions are present (i.e., est.rf() was used), these are revised appropriately; previously they had been removed. Also added err and map.function arguments, to be passed to est.map() when the map is re-estimated.
Revised scanone() and scantwo() slightly; the statement for producing a warning regarding the use of method==“im” (vs “imp” or “em”) was slightly wrong.
Fixed a slight bug in scanqtl() for the case that a fixed position is provided rather than a range (commented out two lines).
summary.cross() now prints a warning if $data objects are data frames. (They should be simple matrices.)
summary.cross() now prints a warning message if the genetic maps are not matrices with 2 rows for “f2ss” and “4way” crosses, or are matrices for other crosses.
drop.markers() now prints a warning if some markers were not found.
Added arguments ylim and add.legend to the function effectplot().
Added arguments xlim and mtick to function plot.scanone(). (mtick allows marker locations to be indicated by triangles rather than line segments.)
Fixed a bug in read.cross for the case that phenotypes have values like “1x2”.
Fixed a slight bug in write.cross for the qtlcart format.
Fixed a bug in read.cross for the qtlcart format regarding the determination of whether a chromosome is autosomal or the X. (Previously, looked for an “X” or “x” in the marker names; now look at whether the chromosome names contains an “X” or “x”.)
Fixed a bug in makeqtl() for the case of a four-way cross. (Hadn’t dealt properly with sex-specific maps.
fitqtl() now stops with a more meaningful error message if imputed genotypes are not available in the input “qtl” object.
Revised the marker names for the X chromosome in the map10 dataset that is included.
Revised est.map() for the case of a sex-specific f2 (cross type “f2ss”); the starting map for the EM algorithm is randomized a bit.
Revised a bunch of the R code files so that paste() is not included within stop() or warn().
In a couple of utility functions for the hidden Markov model engine, I need access to the log1p() function, but I’m having trouble with that in Windows. Thus, in Windows only, I use log(1+x) in place of the preferred log1p() function.
Added tests of input/output that are run when doing a check of the package.
Added Listeria data in QTL Cartographer format to the sampledata directory.
Revised read.cross and write.cross for QTL Cartographer format, so that the cross types are converted between those of R/qtl (“f2”, “bc”, “riself”, “risib”) and those of QTL Cartographer (“RI0”, “RI1”, “RI2”, “B1”, “B2”, “SF2”, “RF2”).
Revised read.cross for the Mapmaker format. The map file can now be in a second format, “.maps”, which is created by Mapmaker/exp. The function determines whether it has been presented with the .maps format or the 2- or 3-column tabular format that has been available. Brian Yandell wrote the function to read “.maps” files.
Fixed a small bug in write.cross for the Mapmaker format, and modified the “.prep” file that is created, so that marker distances are no longer included, and including lines "framework chr*".
Revised read.cross with format=“csv”, so that it gives more clear error messages in some cases.
Updated the R/qtl tutorial, rqtltour.pdf. This is now in a directory “docs” in the R/qtl distribution.
Modified the functions scanone and scantwo in order to treat the X chromosome appropriately. Each has a new argument, x.treatment, which indicates how to treat the X chromosome (in particular, whether hemizygous males should be treated the same as homozygous females). For analysis to proceed properly, there should be columns “sex” and “pgm” in the phenotype data, indicating the sex of each individual, and the direction of the cross. See the X chromosome section of the help file for read.cross for more information.
Added another argument to plot.scanone, “lodcolumn”, an integer (or a vector of 3 integers) indicating which columns of the scanone output should be plotted (generally column 3).
Added two functions for plotting phenotypes against marker genotypes. plot.pxg() plots the phenotypes against the genotypes at a single marker. effectplot() plots the average phenotypes against genotypes at one or two markers (or covariates). Also added a function find.marker() which returns the name of the marker closest to a specified position.
Added facilities for analyzing recombinant inbred lines. We now allow two additional cross types, “riself” (RI lines from selfing) and “risib” (RI lines from sibling matings). Added an internal function expand.rf.ri and made important modifications to calc.genoprob, sim.geno, argmax.geno, and est.map. Also modified summary.cross, print.summary.cross, geno.table, replace.map, discan, ripple, scanone, scantwo, makeqtl, calc.errorlod, est.rf, write.cross.mm, write.cross.csv.
Replaced the example fake.f2 with some new data, which includes both males and females and both directions of the intercross, in order to illustrate the proper analysis of the X chromosome.
Modified read.cross and write.cross (and added code from Brian Yandell) to read and write data in QTL Cartographer format.
Fixed a bug in read.cross; the “genotypes” argument needs to have “C” and “D” reversed. “C” = “not BB” = 5 internally; “D” = “not AA” = 4 internally. Thanks to Martin Grandona for identifying the problem.
Fixed a bug in read.cross for format “csv”: an error occurred if marker positions were not given and the first individual was missing a phenotype. Thanks to Justin Borevitz and Norman Warthmann for identifying the problem.
Fixed a bug in fitqtl. Also added type III sums of squares table and also nominal P-values.
Revised the read.cross functions so that if the X chromosome data is coded as A:B, it gets re-coded appropriately.
Revised read.cross.mm and read.cross.csv so that if marker positions are included, marker order is taken according to those positions. (Previously, read.cross stopped with an error.)
Added some additional example data, bristle3 and bristleX, from Long et al. (1995) Genetics 139:1273-1291.
Added an example genetic map, map10, containing 19 autosomes and an X chromosome, with chromosome lengths approximately as in the mouse and markers at approximately 10 cM spacing.
Changed web references “biosun01.biostat.jhsph.edu” to “www.biostat.jhsph.edu”.
Revised summary.cross to print an error if the cross type is not one of “f2”, “f2ss”, “bc”, “4way”, “risib”, or “riself”.
Revised plot.map so that, when genetic maps are plotted vertically, the 1st marker is at the top (rather than at the bottom).
Modified scanone and scantwo to include the methods “mr-imp” and “mr-argmax”, for performing “marker regression” by first filling in any missing genotypes by one imputation (“mr-imp”) or using the Viterbi algorithm (“mr-argmax”).
Edited functions read.cross.*, argmax.geno, sim.cross, and sim.draws, so that the data, argmax and draws portion of a cross object are stored as integers. This can save considerable space.
Added functions to perform a general scan by imputation: fitqtl(), makeqtl(), scanqtl().
Edited the read.cross.* functions again; now by default dir = "" rather than “.”, and I no longer remove any trailing “/” from dir.
Added checks of genotype values in the function summary.cross.
Rather than edit the read.cross function to read in X chromosome data appropriately, I instead edited its help file, to explain that X-linked data should be coded as an autosome in a backcross (with genotypes A and H).
Fixed slight errors in the functions scanone, calc.genoprob, discan, calc.pairprob, and sim.geno regarding the naming of the genotypes for the 4-way cross.
Changed a couple of apostrophes to double-quotes in the function summary.scantwo.
Added a Morgan map function (mf.m and imf.m), with revisions to argmax.geno, calc.genoprob, calc.pairprob, calc.errorlod, est.map, ripple, sim.geno, sim.cross, sim.cross.bc, sim.cross.f2, sim.cross.4way, fill.geno.
Fixed a slight bug in ripple regarding the estimated chromosome lengths in the case of a 4-way cross; I was picking out the wrong element of the map.
Fixed a bug in plot.scantwo regarding chromosome labels.
Fixed bugs in max.scantwo and scantwo.perm regarding infinite LOD scores (which comes up especially when running scantwo with method=“mr”).
Fixed a bug in read.cross.qtx regarding the determination of whether a cross is a backcross or an intercross. Also fixed the case of a backcross coded as H:B rather than A:H.
Added a warning in summary.cross regarding duplicate markers.
Modified the example cross data (such as hyper and listeria) so that genotypes are stored as integers.
Updated the “README.txt” file, to include explanations for installation of R and R/qtl on Mac OS.
Changed the default for the na.strings argument in read.cross and read.cross.csv to include “NA”.
Changed a couple of lines in write.cross.csv and write.cross.mm for the treatment of NA strings.
Modified ripple so that orders considered are printed in a way that the left-most marker in the original order is always to the left of the right-most marker in the original order.
In various functions, made sure that 0 < error.prob < 1.
Edited plot.scanone so that when only one chromosome is plotted, the chromosome number doesn’t appear at the top, and when multiple chromosomes are plotted, the chromosome numbers appear at the bottom, rather than cumulative cM position.
Changed the addcov and intcov arguments to scanone and scantwo to addcovar and intcovar, respectively.
Added ability to read data in Mapmanager QTX format. This may be done via the read.cross function by using the argument format=“qtx”. Added a file in this format to the sampledata directory distributed with R/qtl.
Modified function ripple(), which compares marker orders, so that it may evaluate counts of obligate crossovers, which will be extremely quick relative to performing an exact likelihood calculation. This method has been made the default.
Added functions max.scanone and max.scantwo for getting information on the location with the highest LOD or joint and interaction LODs
Modified summary.scantwo so that if the argument thresholds has length 1, the interaction and conditional thresholds are assumed to be 0 (so that all chromosome pairs for which the maximum joint LOD is greater than the given threshold are printed).
Revised the C functions emit_bc(), emit_f2(), emit_f2ss() and emit_4way() so that unexpected observed genotypes are treated as missing.
Revised read.cross, read.cross.csv and read.cross.mm slightly, so that estimate.map is TRUE by default, and so that the genetic maps are re-estimated only if both estimate.map is TRUE and the genetic map is missing from the input files. If estimate.map is FALSE and the genetic map is missing from the input files, a dummy genetic map is inserted.
Fixed a bug in sim.cross, sorting the “model” matrix in advance of performing the simulation, because the results were erroneous if QTLs were specified out of order.
Edited the functions read.cross.* to use the function file.path() to create file names.
In read.cross.mm and read.cross.csv, when using the function read.table, we replaced the use of as.is=TRUE with colClasses=“character”. Apparently as.is=TRUE didn’t work in R version 1.4.0.
In read.cross, changed the default of the argument “estimate.map” to FALSE.
Fixed a problem with chromosome labels in plot.scantwo.
Fixed a slight bug in summary.ripple.
Previously forgot to implement the use of the “main” arg for plot.scanone.
Fixed a slight bug in read.cross.gary related to having just one marker on a chromosome.
Fixed a slight bug in plot.cross for the case auto.layout=FALSE.
Revised read.cross so that, for the csv format, if the argument “genotypes” is NULL, the genotypes are assumed to be correct. If there are genotypes > 5, it is assumed to be a 4-way cross.
For some reason, the wrapper for est_map for 4-way crosses got deleted. I’ve re-written it. Hopefully it works!
Fixed a slight bug in plot.map for plotting two sex-specific maps. (The function works by pulling apart the sex-specific maps and then calling plot.map again twice. After those calls, it should return.)
Expanded examples in the help file for fake.4way.
Fixed a bug in create.map for sex-specific maps.
Revised calc.genoprob, argmax.geno and sim.geno so that, in the case of one marker on a chromosome, off.end is forced to be > 0.
Revised plot.scanone so that if there is exactly one LOD score for a chromosome, a small segment is plotted rather than a dot.
Fixed a couple of minor bugs in read.cross for the mapmaker format: in dealing with the “symbols” information in the mapmaker file, and in counting the number of lines in the file.
Added a utility function checkcovar() to check phenotypes and covariates in scanone and scantwo (thus removing some redundancy).
Replaced the example data fake.bc with something that will allow the illustration of the use of covariates.
Added print.summary.ripple; I’d forgotten to write it before.
Added an updated tutorial on R/qtl, distributed as the file rqtltour.pdf
Consolidated scanone, vbscan and discan into the single function scanone, with an argument model=c(“normal”,“binary”,“2part”,“np”). The non-parametric “method” is now a “model”.
Buried scanone.perm and scantwo.perm as internal functions. To do permutation tests, one now uses the main functions (such as scantwo) and specifies the n.perm argument.
Similarly, read.cross.* and write.cross.* were buried, so that the user is expected to call either read.cross or write.cross rather than calling the format-specific functions directly. This was done anticipating an increase in the number of such format-specific read.cross functions.
Got rid of find.errors and plot.errors, as I don’t like them. Use calc.errorlod and plot.errorlod instead.
Wanted to toss pull.chr, but instead just kept an internal version which calls subset.cross and prints a warning, in case our one official user has code which requires it.
Added an “eq.spacing” argument to sim.map for generating maps with equally-spaced markers. This seems more useful than putting them down at random.
Re-wrote a great deal of the help documentation (especially the examples and details).
Added a new example data set, badorder, with some errors in marker order. (This is to illustrate the functions est.rf, ripple and switch.order.)
Fixed a slight error in summary.scantwo. We print pairs of loci only if their joint LOD exceeds its threshold and either (a) the epistasis LOD exceeds its threshold or (b) both conditional LODs exceed their thresholds.
Totally re-wrote print.summary.scantwo. It was unnecessarily complicated before.
Made a very slight change regarding the zlim in plot.scantwo.
Fixed scantwo, summary.scantwo and plot.scantwo to deal with cases of bad LOD scores (NAs, negative numbers and Infs). A warning message will always be printed.
Modified scanone_imp.c so that nullRss and altRss don’t allocate memory each time. Fixed a very bad bug in dealing with interactive covariates. Fixed a single-character bug in scantwo_mr.c that was causing a core dump.
Added a scantwo function to do two-dimensional genome scans, calculating LOD scores for a two-QTL model and to test epistasis between each pair, with calculations done by imputation, Haley-Knott regression, marker regression or the EM algorithm. Hao Wu wrote the imputation method.
With Hao Wu, wrote plot.scantwo to plot the results of scantwo, summary.scantwo to summarize the results, and scantwo.perm to get genome-wide LOD thresholds for a 2-dimensional genome scan by permutation tests. The summary.scantwo function uses a criterion due to Gary Churchill and Saunak Sen.
Added a C function to calculate joint genotype probabilities for pairs of putative QTLs on the same chromosome. Because the resulting set of probabilities can take up a lot of memory, we’re not going to make these accessible to the user. The function calc.pairprob was created, but this is not to be called by the user, but rather will be called when needed.
Added a “method” argument to vbscan, even though only method=“em” is currently available.
Revised scanone, scantwo, discan, vbscan, and their corresponding “.perm” functions so that the output has attribute “method” to indicate what method was used and attribute “type” to indicate the type of cross that was analyzed.
Changed method=“im” to method=“em” in scanone and discan; changed method=“markreg” again, this time to method=“mg”. Changed the order of these methods in scanone.
calc.genoprob now includes an attribute “map.function” with the probabilities.
Changed colors plotted in plot.rf.
Modified the C function scanone_mr (marker regression) to avoid repeatedly running the null model regression in the case of complete marker data.
Changed a good amount of R code like “1:length(x)” to “seq(along=x)”
Added a function fill.geno for imputing missing marker data by simulation (through sim.geno) or by the Viterbi algorithm (through argmax.geno), so that one may perform quick-and-dirty (with an emphasis on dirty) genome scans by marker regression.
Fixed a small bug in sim.cross.f2.
Fixed some problems related to chromosomes with only one marker: read.cross.csv, create.map, subset.cross.
Fixed a bug in the location of chromosome labels in plot.scanone. Added an argument “main” for placing a title on the plot.
Revised lots of little pieces of code using “drop=FALSE” when subsetting a matrix or array in order to retain the structure.
read.cross.csv can now deal with categorical phenotypes, and plot.cross was revised to deal with such non-numeric phenotypes. Added an argument “auto.layout”; if TRUE, mfrow is set so that the many plots produced will all fit in one figure. par(ask=TRUE) is no longer ever set.
Revised sim.cross so that when keep.qtlgeno=TRUE, the QTL genotypes are retained in a component cross$qtlgeno (rather than within the data matrices).
Hao Wu (hao@jax.org) has implemented the imputation method of Sen and Churchill (2001) for a genome scan, included as method=“imp” in the function scanone.
Added a non-parametric method to the function scanone, using a modified version of the Kruskal-Wallis test (cf Kruglyak and Lander 1995).
scanone now allows the use of covariates for all methods except the non-parametric method.
Phenotypes in a cross object are now a data.frame. Modified example data files and the following functions to make this work: sim.cross., read.cross., summary.cross, write.cross.csv.
Changed the name of the “anova” method in scanone to “markreg”.
Changed the name of the argument “print.rf” in the est.map function to “trace.”
Modified the default cutoff in top.errorlod; allow cuts and colors in plot.errorlod to be specified by the user.
summary.cross() now checks that markers are in increasing order.
Made the third row (marker positions) in csv file optional in read.cross.csv.
Added a utility function subset.cross() for pulling out specified chromosomes or groups of individuals from a cross object. We should not need pull.chr() any longer.
Added a utility function c.cross() for concatenating multiple cross objects.
Changed stopping rules for discan, discan.perm, vbscan, vbscan.perm, est.map, est.rf, ripple, scanone, scanone.perm: |x(s+1) - x(s)| < e {|x(s)| + e*100} where by default e = 1e-4
Fixed the utility function create.map() for the case where the genetic map starts at somewhere other than 0.
Placed help information for discan.perm, scanone.perm and vbscan.perm within the files for discan, scanone and vbscan, respectively.
Fixed a real bug in argmax.geno().
Added discan() for doing interval mapping with a dichotomous trait.
Added documentation for the print.summary.* and internal functions.
Edited documentation files to conform to R guidelines.
Reduced the minimum value of the error.prob argument in est.map, calc.genoprob, argmax.geno and sim.geno from 1e-14 to 1e-50.
Tried to fix up some of the plot.* and summary.* functions so that I don’t get warning messages in “R CMD check”.
Fixed a few minor problems in the help files.
Updated the a.starting.point() help file.
Fixed a couple of problems in marker order in the hyper data.
Added plot.info() for plotting the proportion of missing information in the genotype data.
Fixed bug in plot.scanone() that led to problems in overlaying LOD curves using add=TRUE. Added an argument, gap, to specify the distance between chromosomes.
Fixed bug in print.summary.scanone() that resulted in an error when there was just one chromosome with LOD above the specified threshold.
Fixed slight error in sim.cross(); marker genotypes were removed rather than qtl genotypes. We now use the function drop.qtlgeno() to do this.
Changed anova method in scanone() to use observed genotypes. Individuals with missing or partially missing genotypes are dropped.
Added Haley-Knott regression method to scanone().
Added a function ripple() for comparing marker orders for a single chromosome, looking at all permutations of a sliding window of markers. Also added switch.order() to switch the order of markers on a specified chromosome.
Removed null markers from listeria data.
Fixed bugs in read.cross.mm() and write.cross.mm().
Added csv and mapmaker format files to sample data directory.
Allow specification of starting value is scanone and vbscan
Added a document “rqtltour.pdf” describing the package and giving a couple of examples.
Fixed a very slight bug in summary.scanone().
Changed the argument “which.chr” in plot.scanone() to simply “chr”.
Added a “chr” argument to plot.missing().
Added write.cross.csv(), for writing data in comma-delimited format. Changed write.mm() to write.cross.mm() and added write.cross() as a wrapper to these two functions.
All functions that use map functions now allow use of the Carter-Falconer map function.
Changed remove.markers(), remove.nullmarkers(), and remove.qtlgeno() to drop.markers(), drop.nullmarkers() and drop.qtlgeno().
Revised plot.rf() so that missing values appear in gray.
Added read.cross.gary(), to read data in Gary’s format, and read.cross.csv(), to read data in comma-delimited format.
Fixed the bugs in read.cross.mm(); see BUGS.txt.
Fixed summary.cross() so that it checks marker names in the data and the map.
Added summary.scanone(), giving a summary of the output of scanone().
Added possibility of F2 intercross with sex-specific maps. Use class “f2ss” rather than “f2.” This is in the testing stage. The only revised functions, at this point, are est.map() and calc.genoprob().
Added a function convert2ss() to convert a cross object from “f2” to “f2ss” format.
plot.scanone can now plot three scanone outputs, and includes an “add” argument for adding additional outputs to a current plot.
Replaced 1e-10 with 1e-14 as tolerance value for error probability and minimum map distance.
Changed the “min.d” argument in plot.geno() to “min.sep”, taken to be a percent of the chromosome length.
Added Carter-Falconer map function: mf.cf() and imf.cf(). Note that there is no closed-form version of mf.cf(), and so I use the R function uniroot().
Fixed a slight error in replace.map().
In est.map, calculate the log likelihood at the end; this is saved as an attribute, “loglik” for each chromosome’s map. If the “print” argument is used, print the loglik, too.
Made error.prob=0 the default for the functions argmax.geno(), calc.genoprob(), est.map(), and sim.geno().
Fixed the file permissions for many of the files, so that they are readable by all users.
Eliminated the map component of the results of calc.genoprob, argmax.geno, and sim.geno. Since we are now including attributes “error.prob,” “step,” and “off.end,” we can just use create.map() to recreate the map each time, without having to carry it along.
Changed the name of plot.geno() to plot.missing() and plot.chr() to plot.geno().
Added vbscan() and vbscan.perm() to perform the analysis described in V Boyartchuk et al. (2001), for a phenotype where some individuals have some quantitative phenotype, while for others it is undefined. (Examples: the size of a lesion, where some individuals exhibit no lesion; time-to-death after an infection, where some individuals recover from the infection.)
Added map functions (and inversion map functions) for Haldane and Kosambi, so that I’m not re-creating them all of the time within functions.
Added a function plot.chr() to plot genotypes for a specific chromosome, with likely errors (as determined by calc.errorlod() or find.errors()) highlighted.
Added a warning to the help file for argmax.geno. The results greatly depend on the value of the step argument, and may not be terribly trustworthy. Also, if several sequences (of underlying genotypes) are all most likely, our method of randomly choosing among them is not right…recombination events are too far to the right.
Fixed a small bug in create.map(), which is used by calc.genoprob(). An error occurred in the case of a genetic map with equally spaced markers, when the argument “step” was set to be exactly the inter-marker distance.
Modified calc.genoprob(), calc.argmax(), sim.geno() and calc.errorlod() so that their corresponding components have attributes “error.prob”, “step” and “off.end” (only “error.prob” for calc.errorlod()), specifying the corresponding values used in the calculations. Modified calc.errorlod() to re-run calc.genoprob() if the error.prob attribute is different from the corresponding argument.
This is a totally revised version of the package. Most importantly, the data structure for a cross has completely changed. The function convert.cross is included, for converting data from the old structure to the new one. See the help file for read.cross for a description of the new data structure.
The main hidden Markov model engine has been rewritten, to make things more flexible and general. We’ve now implemented the Viterbi algorithm, in the function argmax.geno, to calculate the most likely sequence of underlying genotypes, given the observed marker data, and we’ve fixed the calculation of the Lincoln and Lander error LOD scores. The analysis of phase-known four-way crosses is now possible.
The “singlescan” function (to do a genome scan with a single QTL model) is now called “scanone” (to save a few keystrokes). Note that this function does not yet allow the use of covariates. We’ll add that feature in the near future.
Saunak Sen and I are now working together on this project, and so things will begin to progress more quickly (we hope).