Package: TCC 1.47.0

Jianqiang Sun

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

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.

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

TCC_1.47.0.tar.gz
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TCC_1.47.0.tgz(r-4.4-any)TCC_1.47.0.tgz(r-4.3-any)
TCC_1.47.0.tar.gz(r-4.5-noble)TCC_1.47.0.tar.gz(r-4.4-noble)
TCC_1.47.0.tgz(r-4.4-emscripten)TCC_1.47.0.tgz(r-4.3-emscripten)
TCC.pdf |TCC.html✨
TCC/json (API)
NEWS

# Install 'TCC' in R:
install.packages('TCC', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • arab - Arabidopsis RNA-Seq data set
  • hypoData - A simulation dataset for comparing two-group tag count data, focusing on RNA-seq
  • hypoData_mg - A simulation dataset for comparing three-group tag count data, focusing on RNA-seq
  • hypoData_ts - A sample microarray data for detecting tissue-specific patterns.
  • nakai - DNA microarray data set

On BioConductor:TCC-1.47.0(bioc 3.21)TCC-1.46.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologysequencingdifferentialexpressionrnaseq

5.40 score 42 scripts 504 downloads 67 mentions 18 exports 76 dependencies

Last updated 2 months agofrom:8a4c02e13c. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 25 2024
R-4.5-winNOTENov 25 2024
R-4.5-linuxNOTENov 25 2024
R-4.4-winNOTENov 25 2024
R-4.4-macNOTENov 25 2024
R-4.3-winNOTENov 25 2024
R-4.3-macNOTENov 25 2024

Exports:[calcAUCValuecalcNormFactorsclusterSampleestimateDEfilterLowCountGenesgetNormalizedDatagetResultlengthmakeFCMatrixnamesplot.TCCplotFCPseudocolorROKUshow.TCCsimulateReadCountsTCCWAD

Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelclicodetoolscolorspacecpp11crayoncurlDelayedArrayDESeq2edgeRevaluatefansifarverformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehighrhttrIRangesisobandjsonliteknitrlabelinglambda.rlatticelifecyclelimmalocfitmagrittrMASSMatrixMatrixGenericsmatrixStatsmgcvmimemunsellnlmeopensslpillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangROCS4ArraysS4VectorsscalessnowSparseArraystatmodSummarizedExperimentsystibbleUCSC.utilsutf8vctrsviridisLitewithrxfunXVectoryamlzlibbioc

TCC

Rendered fromTCC.Rnwusingutils::Sweaveon Nov 25 2024.

Last update: 2024-01-03
Started: 2013-11-01

Readme and manuals

Help Manual

Help pageTopics
Arabidopsis RNA-Seq data setarab
Calculate AUC value from a TCC-class objectcalcAUCValue
Calculate normalization factorscalcNormFactors calcNormFactors,DGEList-method calcNormFactors,TCC-method
Perform hierarchical clustering for samples from expression dataclusterSample
Estimate degrees of differential expression (DE) for individual genesestimateDE
Filter genes from a TCC-class objectfilterLowCountGenes
Obtain normalized count datagetNormalizedData
Obtain the summaries of results after the differential expression analysisgetResult
A simulation dataset for comparing two-group tag count data, focusing on RNA-seqhypoData
A simulation dataset for comparing three-group tag count data, focusing on RNA-seqhypoData_mg
A sample microarray data for detecting tissue-specific patterns.hypoData_ts
Generate the fold change matrix for simulating count datamakeFCMatrix
DNA microarray data setnakai
Plot a log fold-change versus log average expression (so-called M-A plot)plot plot.TCC
Create a pseudo-color image of simulation dataplotFCPseudocolor
detect tissue-specific (or tissue-selective) patterns from microarray data with many kinds of samplesROKU
Generate simulation data from negative binomial (NB) distributionsimulateReadCounts
A package for differential expression analysis from tag count data with robust normalization strategiesTCC-package TCC
A container for storing information used in TCClength length,TCC-method names names,TCC-method show show,TCC-method show.TCC subset subset,TCC-method TCC-class [ [,TCC,ANY,ANY,ANY-method [,TCC,ANY,ANY-method [,TCC,ANY-method [,TCC-method
Calculate WAD statistic for individual genesWAD