Package: tempoR
Title: Characterizing Temporal Dysregulation
Version: 1.0.4.4
Authors@R: person("Christopher", "Pietras", email = "christopher.pietras@tufts.edu", role = c("aut", "cre"))
Description: TEMPO (TEmporal Modeling of Pathway Outliers) is a pathway-based outlier detection approach for finding pathways showing 
    significant changes in temporal expression patterns across conditions.  Given a gene expression data set where each sample is characterized by 
    an age or time point as well as a phenotype (e.g. control or disease), and a collection of gene sets or pathways, TEMPO ranks each pathway
    by a score that characterizes how well a partial least squares regression (PLSR) model can predict age as a function of gene expression in the controls
    and how poorly that same model performs in the disease. TEMPO v1.0.3 is described in Pietras (2018) <doi:10.1145/3233547.3233559>.
Depends: R (>= 3.0.2)
Imports: doParallel (>= 1.0.10), foreach (>= 1.4.3), parallel (>=
        3.0.2), pls (>= 2.5.0), grDevices, graphics, stats, utils
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-24 18:10:04 UTC; cmpietras
Author: Christopher Pietras [aut, cre]
Maintainer: Christopher Pietras <christopher.pietras@tufts.edu>
Repository: CRAN
Date/Publication: 2019-05-27 08:30:03 UTC
Built: R 3.5.3; ; 2020-04-22 06:35:30 UTC; windows
