sabarsi: Background Removal and Spectrum Identification for SERS Data
Implements a new approach 'SABARSI' described in Wang et al., "A Statistical Approach of Background Removal and Spectrum Identification for SERS Data" (Unpublished).
Sabarsi forms a pipeline for SERS (surface-enhanced Raman scattering) data analysis including background removal, signal detection, signal integration, and cross-experiment comparison. The background removal algorithm, the very first step of SERS data analysis, takes into account the change of background shape.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats (≥ 3.5.0) |
| Suggests: |
knitr, rmarkdown (≥ 1.13) |
| Published: |
2019-08-08 |
| Author: |
Li Jun [cre],
Wang Chuanqi [aut] |
| Maintainer: |
Li Jun <jun.li at nd.edu> |
| License: |
GPL-3 |
| NeedsCompilation: |
no |
| CRAN checks: |
sabarsi results |
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