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\name{LogNMulti}
\alias{LogNMulti}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
EM algorithm for the NB-beta model in the multiple condition test
}
\description{
'LogNMulti' specifies the function to run (one round of) the EM algorithm for the NB-beta model in the multiple condition test.}
\usage{
LogNMulti(Input, InputSP, EmpiricalR, EmpiricalRSP,
NumOfEachGroup, AlphaIn, BetaIn, PIn,
NoneZeroLength, AllParti, Conditions)
}
\arguments{
\item{Input, InputSP}{The expressions among all the samples.}
\item{NumOfEachGroup}{Number of genes in each Ng group.}
\item{AlphaIn, PIn, BetaIn, EmpiricalR, EmpiricalRSP}{The parameters from the last EM step.}
\item{NoneZeroLength}{Number of Ng groups.}
\item{AllParti}{The patterns of interests.}
\item{Conditions}{The condition assignment for each sample.}
}
\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)
}
\author{
Ning Leng
}
\examples{
#
#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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