An R package for Gene and Isoform Differential Expression Analysis On RNA-Seq Data


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Documentation for package ‘EBSeq’ version 1.1.4

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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
BuildTree Hierachical Clustering based on EBSeq DE analysis
CheckNg CheckNgStructure
crit_fun Calculate the adjusted FDR threshold
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 multiple condition study
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 Predictive Distribution of being EE
f1 f1(Input, AlphaIn, BetaIn, EmpiricalR, NumOfGroups, log)
GeneEBresultGouldBart2 The EBSeq result of the empirical gene data ( Gould Lab data, bart2 )
GeneMat The simulated data for two condition gene DE analysis
GeneMultiSimu Gene Level Simulation for multiple conditions
GeneSimu Gene Level Simulation
GeneSimuAt Gene Level Simulation with outliers
GetData Read in RSEM output of Gould data
GetMultiFC Calculate the Fold Changes for each pair of conditions
GetMultiPP Generate the Posterior Probability of each transcript.
GetNg Generate the Ng vector
GetPatterns Generate all possible patterns in multiple condtion study
GetPP Generate the Posterior Probability of each transcript.
GetPPMat Generate the Posterior Probability of each transcript.
GetR Calculate the R
IsoEBresultGouldBart2 The EBSeq result of the empirical isoform data ( Gould Lab data, bart2 )
IsoList The simulated data for two condition isoform DE analysis
IsoSimu Isoform level simulation
IsoSimuAt Isoform level simulation with outliers
Likefun Likelihood Function of the NB-Beta Model
LikefunMulti Likelihood Function of the NB-Beta Model
LogN The function to run EM (one round) using optim.
LogNMulti The function to run EM (one round) using optim.
MedianNorm Median Normalization
MergeGene Plots of gene simulation result
MergeIso Isoforms of gene simulation result
MultiGeneMat The simulated data for multiple condition gene DE analysis
PlotPattern Visualize the patterns
PlotPostVsRealFC Plot Posterior FC vs FC
PlotTree Plot the dendrograph of the hierachical cluster results from EBSeq
PolyFitPlot Fit the mean-var relationship using polynomial regression
PoolMatrix Generate the expression matrix from the output of GetData
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
WithinDE Test each sample with the other ones