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

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Documentation for package ‘EBSeq’ version 2.7.0

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