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TCC

TCC: Differential expression analysis for tag count data with robust normalization strategies

Bioconductor version: 3.23 · Package version: 1.52.0

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.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("TCC")

Details

MaintainerJianqiang Sun <sun@bitdessin.dev>, Tomoaki Nishiyama <tomoakin@staff.kanazawa-u.ac.jp>
AuthorJianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota
LicenseGPL-2
Downloads rank609
Source branchRELEASE_3_23
biocViewsDifferentialExpression, ImmunoOncology, RNASeq, Sequencing, Software

Documentation

Download

Dependencies

Depends: R (>= 3.0), methods, DESeq2, edgeR, ROC

Suggests: RUnit, BiocGenerics

Reverse dependencies

Suggests Me (1): compcodeR