cormotiffitfull: Full Model Motif Fit In Cormotif: Correlation 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

 `1` ```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.

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).

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.

Author(s)

Hongkai Ji, Yingying Wei

References

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 Unpublished

Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```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) ```

Cormotif documentation built on April 29, 2020, 5:20 a.m.