Cormotif (version 1.18.0)

cormotiffitfull: Full Model Motif Fit

Description

This function fits the data to the model with all $2^D$ possible 0-1 patterns, where $D$ is the number of studies.

Usage

cormotiffitfull(exprs,groupid,compid, tol=1e-3, max.iter=100)

Arguments

exprs

a matrix, the expression data after normalization that is on log2 scale, each row of the matrix corresponds to a gene and each column of the matrix corresponds to a sample array.

groupid

the group label for each sample array, two arrays in the same study with same experinment condition$(e.g. control)$ have the same groupid.

compid

the study design and comparison matrix, each row of the matrix corresponds to one study with the first column being the first experinment condition and the second column being the second experinment condition

tol

the relative tolerance level of error.

max.iter

maximun number of iterations.

Value

p.post

the posterior probability for each gene to be differentially expressed.

motif.prior

fitted values of the probability distribution of the $2^D$ 0-1 motifs.

loglike

log-likelihood of the fitted model.

Details

The difference between $cormotiffitfull$ and $cormotif(...,K=2^D,...)$ is that $cormotiffitfull$ forces motif to be one of the those 0-1 patterns. For $cormotiffit$, the motif does not necessarily to be of either 1 or 0, such as (0,1,..,0). It could be (0.9,0.4,...,0.2).

References

Ji, H., Wei, Y.,(2011) Correlation Motif. Unpublished

Examples

data(simudata2)
n<-nrow(simudata2)
m<-ncol(simudata2)
#the expression data is from the second column to m
exprs.simu2<-as.matrix(simudata2[,2:m])

#prepare the group ID number for each sample array
data(simu2_groupid)

#prepare the design matrix for each group of samples
data(simu2_compgroup)

#fit 2^D 0-1 motifs to the data
motif.fitted.sep<-cormotiffitfull(exprs.simu2, simu2_groupid,simu2_compgroup)