TCC

DOI: 10.18129/B9.bioc.TCC  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see TCC.

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

Bioconductor version: 3.17

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>

Citation (from within R, enter citation("TCC")):

Installation

To install this package, start R (version "4.3") 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

PDF   Reference Manual

Details

biocViews DifferentialExpression, ImmunoOncology, RNASeq, Sequencing, Software
Version 1.40.0
In Bioconductor since BioC 2.13 (R-3.0) (10 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
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/TCC
Source Repository (Developer Access) git clone [email protected]:packages/TCC
Package Short Url https://bioconductor.org/packages/TCC/
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