Package: EBSeq 2.11.0

Xiuyu Ma

EBSeq: An R package for gene and isoform differential expression analysis of RNA-seq data

Differential Expression analysis at both gene and isoform level using RNA-seq data

Authors:Xiuyu Ma [cre, aut], Ning Leng [aut], Christina Kendziorski [ctb], Michael A. Newton [ctb]

EBSeq_2.11.0.tar.gz
EBSeq_2.11.0.zip(r-4.7)EBSeq_2.11.0.zip(r-4.6)EBSeq_2.11.0.zip(r-4.5)
EBSeq_2.11.0.tgz(r-4.6-x86_64)EBSeq_2.11.0.tgz(r-4.6-arm64)EBSeq_2.11.0.tgz(r-4.5-x86_64)EBSeq_2.11.0.tgz(r-4.5-arm64)
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EBSeq_2.11.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
EBSeq/json (API)

# Install 'EBSeq' in R:

install.packages('EBSeq', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

c++– GNU Standard C++ Library v3

Datasets:

GeneMat - The simulated data for two condition gene DE analysis
IsoList - The simulated data for two condition isoform DE analysis
IsoMultiList - The simulated data for multiple condition isoform DE analysis
MultiGeneMat - The simulated data for multiple condition gene DE analysis

On BioConductor:EBSeq-2.11.0(bioc 3.24)EBSeq-2.10.0(bioc 3.23)

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

immunooncology statisticalmethod differentialexpression multiplecomparison rnaseq sequencing cpp

7.96 score 6 packages 205 scripts 261 mentions 28 exports 35 dependencies

Last updated from:78a014dabd. Checks:1 ERROR, 11 WARNING, 2 OK. Indexed: yes.

Target	Result	Time
bioc-checks	ERROR	166
linux-devel-arm64	WARNING	174
linux-devel-x86_64	WARNING	186
source / vignettes	OK	188
linux-release-arm64	WARNING	194
linux-release-x86_64	WARNING	181
macos-release-arm64	WARNING	166
macos-release-x86_64	WARNING	196
macos-oldrel-arm64	WARNING	117
macos-oldrel-x86_64	WARNING	296
windows-devel	WARNING	153
windows-release	WARNING	140
windows-oldrel	WARNING	159
wasm-release	OK	150

Exports:beta.mom crit_fun DenNHist EBMultiTest EBSeqTest EBTest f0 f1 GetDEResults GetMultiFC GetMultiPP GetNg GetNormalizedMat GetPatterns GetPPMat GetSelectedPatterns Likefun LikefunMulti LogN LogNMulti MedianNorm PlotPattern PlotPostVsRawFC PolyFitPlot PostFC QQP QuantileNorm RankNorm

Dependencies:BH bitops blockmodeling brio callr caTools cli crayon desc diffobj evaluate fs glue gplots gtools jsonlite KernSmooth lattice lifecycle magrittr Matrix otel pkgbuild pkgload praise processx ps R6 Rcpp RcppEigen rlang rprojroot testthat waldo withr

EBSeq Vignette

Rendered fromEBSeq_Vignette.Rnwusingutils::Sweave

Last update: 2023-06-16
Started: 2013-11-01

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
EBSeq: RNA-Seq Differential Expression Analysis on both gene and isoform level	EBSeq_NingLeng-package EBSeq_NingLeng
Fit the beta distribution by method of moments	beta.mom
Calculate the soft threshold for a target FDR	crit_fun
Density plot to compare the empirical q's and the simulated q's from the fitted beta distribution.	DenNHist
Using EM algorithm to calculate the posterior probabilities of interested patterns in a multiple condition study	EBMultiTest
EBSeq core	EBSeqTest
Using EM algorithm to calculate the posterior probabilities of being DE	EBTest
The Prior Predictive Distribution of being EE	f0
The Prior Predictive Distribution of being DE	f1
The simulated data for two condition gene DE analysis	GeneMat
Obtain Differential Expression Analysis Results in a Two-condition Test	GetDEResults
Calculate the Fold Changes for Multiple Conditions	GetMultiFC
Posterior Probability of Each Transcript	GetMultiPP
Ng Vector	GetNg
Calculate normalized expression matrix	GetNormalizedMat
Generate all possible patterns in a multiple condition study	GetPatterns
Posterior Probability of Transcripts	GetPPMat
Get selected patterns in a multiple condition study	GetSelectedPatterns
The simulated data for two condition isoform DE analysis	IsoList
The simulated data for multiple condition isoform DE analysis	IsoMultiList
Likelihood Function of the NB-Beta Model	Likefun
Likelihood Function of the NB-Beta Model In Multiple Condition Test	LikefunMulti
The function to run EM (one round) algorithm for the NB-beta model.	LogN
EM algorithm for the NB-beta model in the multiple condition test	LogNMulti
Median Normalization	MedianNorm
The simulated data for multiple condition gene DE analysis	MultiGeneMat
Visualize the patterns	PlotPattern
Plot Posterior FC vs FC	PlotPostVsRawFC
Fit the mean-var relationship using polynomial regression	PolyFitPlot
Calculate the posterior fold change for each transcript across conditions	PostFC
The Quantile-Quantile Plot to compare the empirical q's and simulated q's from fitted beta distribution	QQP
Quantile Normalization	QuantileNorm
Rank Normalization	RankNorm