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TCC (version 1.12.1)

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

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.

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Version

Monthly Downloads

62

Version

1.12.1

License

GPL-2

Maintainer

Last Published

February 15th, 2017

Functions in TCC (1.12.1)

WAD

Calculate WAD statistic for individual genes
clusterSample

Perform hierarchical clustering for samples from expression data
estimateDE

Estimate degrees of differential expression (DE) for individual genes
plot

Plot a log fold-change versus log average expression (so-called M-A plot)
calcNormFactors

Calculate normalization factors
filterLowCountGenes

Filter genes from a TCC-class object
hypoData_mg

A simulation dataset for comparing three-group tag count data, focusing on RNA-seq
nakai

DNA microarray data set
ROKU

detect tissue-specific (or tissue-selective) patterns from microarray data with many kinds of samples
getNormalizedData

Obtain normalized count data
getResult

Obtain the summaries of results after the differential expression analysis
arab

Arabidopsis RNA-Seq data set
calcAUCValue

Calculate AUC value from a TCC-class object
hypoData

A simulation dataset for comparing two-group tag count data, focusing on RNA-seq
plotFCPseudocolor

Create a pseudo-color image of simulation data
TCC

A package for differential expression analysis from tag count data with robust normalization strategies
TCC-class

A container for storing information used in TCC
hypoData_ts

A sample microarray data for detecting tissue-specific patterns.
simulateReadCounts

Generate simulation data from negative binomial (NB) distribution
makeFCMatrix

Generate the fold change matrix for simulating count data