Package: DEqMS
Version: 1.4.0
Date: 2019/04/05
Title: a tool to perform statistical analysis of differential protein
        expression for quantitative proteomics data.
Author: Yafeng Zhu
Maintainer: Yafeng Zhu <yafeng.zhu@outlook.com>
Depends: R(>= 3.5),graphics,stats,ggplot2,limma(>= 3.34)
Suggests:
        BiocStyle,knitr,rmarkdown,plyr,matrixStats,reshape2,farms,utils,ggrepel,ExperimentHub,LSD
LazyLoad: yes
Description: DEqMS is developped on top of Limma. However, Limma assumes same prior variance for all genes. In proteomics, the accuracy of protein abundance estimates varies by the number of peptides/PSMs quantified in both label-free and labelled data. Proteins quantification by multiple peptides or PSMs are more accurate. DEqMS package is able to estimate different prior variances for proteins quantified by different number of PSMs/peptides, therefore acchieving better accuracy. The package can be applied to analyze both label-free and labelled proteomics data. 
License: LGPL
biocViews: ImmunoOncology, Proteomics, MassSpectrometry, Preprocessing,
        DifferentialExpression,
        MultipleComparison,Normalization,Bayesian
VignetteBuilder: knitr
Packaged: 2019-10-30 03:16:09 UTC; biocbuild
BugReports: https://github.com/yafeng/DEqMS/issues
git_url: https://git.bioconductor.org/packages/DEqMS
git_branch: RELEASE_3_10
git_last_commit: f0adbf1
git_last_commit_date: 2019-10-29
Date/Publication: 2019-10-29
NeedsCompilation: no
Built: R 3.6.1; ; 2019-11-02 02:17:42 UTC; unix
