TCC

DOI: 10.18129/B9.bioc.TCC    

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

Bioconductor version: Release (3.15)

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.

Author: Jianqiang Sun, Tomoaki Nishiyama, Kentaro Shimizu, and Koji Kadota

Maintainer: Jianqiang Sun <wukong at bi.a.u-tokyo.ac.jp>, Tomoaki Nishiyama <tomoakin at staff.kanazawa-u.ac.jp>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("TCC")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("TCC")

 

PDF	R Script	TCC
PDF		Reference Manual
Text		NEWS

Details

biocViews	DifferentialExpression, ImmunoOncology, RNASeq, Sequencing, Software
Version	1.36.0
In Bioconductor since	BioC 2.13 (R-3.0) (9 years)
License	GPL-2
Depends	R (>= 3.0), methods, DESeq2, edgeR, baySeq, ROC
Imports
LinkingTo
Suggests	RUnit, BiocGenerics
SystemRequirements
Enhances	snow
URL
Depends On Me
Imports Me
Suggests Me	compcodeR, ExpHunterSuite
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	TCC_1.36.0.tar.gz
Windows Binary	TCC_1.36.0.zip (64-bit only)
macOS Binary (x86_64)	TCC_1.36.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/TCC
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/TCC
Package Short Url	https://bioconductor.org/packages/TCC/
Package Downloads Report	Download Stats