Package: TCC
Type: Package
Title: TCC: Differential expression analysis for tag count data with
        robust normalization strategies
Version: 1.30.0
Author: Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota
Maintainer: Jianqiang Sun <wukong@bi.a.u-tokyo.ac.jp>, Tomoaki
 Nishiyama <tomoakin@staff.kanazawa-u.ac.jp>
Description: This package provides a series of functions for performing
        differential expression analysis from RNA-seq count data using
        robust normalization strategy (called DEGES). The basic idea of
        DEGES is that potential differentially expressed genes or
        transcripts (DEGs) among compared samples should be removed
        before data normalization to obtain a well-ranked gene list
        where true DEGs are top-ranked and non-DEGs are bottom ranked.
        This can be done by performing a multi-step normalization
        strategy (called DEGES for DEG elimination strategy). A major
        characteristic of TCC is to provide the robust normalization
        methods for several kinds of count data (two-group with or
        without replicates, multi-group/multi-factor, and so on) by
        virtue of the use of combinations of functions in depended
        packages.
Depends: R (>= 3.0), methods, DESeq2, edgeR, baySeq, ROC
Suggests: RUnit, BiocGenerics
Enhances: snow
License: GPL-2
Copyright: Authors listed above
biocViews: ImmunoOncology, Sequencing, DifferentialExpression, RNASeq
git_url: https://git.bioconductor.org/packages/TCC
git_branch: RELEASE_3_12
git_last_commit: 40c62a0
git_last_commit_date: 2020-10-27
Date/Publication: 2020-10-28
NeedsCompilation: no
Packaged: 2020-10-29 03:42:46 UTC; biocbuild
Built: R 4.0.3; ; 2020-10-29 14:04:11 UTC; windows
