EM algorithm for the NB-beta model in the multiple condition test

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Description

'LogNMulti' specifies the function to run (one round of) the EM algorithm for the NB-beta model in the multiple condition test.

Usage

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LogNMulti(Input, InputSP, EmpiricalR, EmpiricalRSP, 
	NumOfEachGroup, AlphaIn, BetaIn, PIn, 
	NoneZeroLength, AllParti, Conditions)

Arguments

Input, InputSP

The expressions among all the samples.

NumOfEachGroup

Number of genes in each Ng group.

AlphaIn, PIn, BetaIn, EmpiricalR, EmpiricalRSP

The parameters from the last EM step.

NoneZeroLength

Number of Ng groups.

AllParti

The patterns of interests.

Conditions

The condition assignment for each sample.

Author(s)

Ning Leng

References

Ning Leng, John A. Dawson, James A. Thomson, Victor Ruotti, Anna I. Rissman, Bart M.G. Smits, Jill D. Haag, Michael N. Gould, Ron M. Stewart, and Christina Kendziorski. EBSeq: An empirical Bayes hierarchical model for inference in RNA-seq experiments. Bioinformatics (2013)

Examples

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#

#Input = matrix(rnorm(100,100,1),ncol=10)
#rownames(Input) = paste("g",1:10)
#RIn = matrix(rnorm(100,200,1), ncol=10)
#res = LogNMulti(Input, list(Input[,1:5], Input[,6:10]),
#	RIn, list(RIn[,1:5], RIn[,6:10]), 10, .6, .7, 
#	c(.3,.7), 1, rbind(c(1,1), c(1,2)), 
#	as.factor(rep(c("C1","C2"), each=5)))

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