mclapply.AIPS: Multicore/parallel function that will assign the AIPS models...

In meoyo/AIPS: AIPS : Absolute Inference of Patient Signatures

Description

Given a gene expression matrix D where rows correspond to genes and columns to samples and a list of Entrez gene ids, this function will assign all the AIPS models by taking advantage of the multicore/parallel package.

Usage

mclapply.AIPS (D, EntrezID, n.cores)

Arguments

D	A matrix D of gene expression. Rows are genes and columns are samples (tumor from breast cancer patients).
EntrezID	A character vector corresponding to the Entrez Ids of the genes of matrix D.
n.cores	Number of CPU (cores) to use to run AIPS. Default is detectCores() - 2

Details

We defined Absolute Inference of Patient Signatures (AIPS) to stabilize the assignement of pathway activation and enable assignment on single whole-tumor and single cell gene expression. The idea of the approach is to use simple rules of the form "if gene A expression < gene B expression assigned sample to subtype X". By using those simple rules we are able to assign pathway activation using only the expression values of one patient or one single-cell profile. We have shown AIPS recapitulates whole-cohort assignments. This function will return the pathway activation assignment as well as the posterior probabilities for all the assignments.

Value

cl	Gene signature activation identified by AIPS. It could be either "low", "random/independent", or "high".
posterior	A vector corresponding to the posterior probabilities of the activation classes in cl.
gs.info	A matrix that contains the information about the gene signatures (Name, Source, Description)
raw.aips	All the individual AIPS assignments

Author(s)

Eric R. Paquet ([e-mail])

References

Paquet ER, Hallett MT. J Natl Cancer Inst. 2014 Dec 4;107(1):357

See Also

aips.models, mcgill.gq

Examples

## Load the McGill dataset used in the paper
data(mcgill.gq)

## Assignd AIPS on the first 5 gene expression in the McGill dataset
mcgill.AIPS <- mclapply.AIPS (mcgill.gq$D[,1:5],
                              mcgill.gq$EntrezID)

## Print a summary of the assignments for AIPS model #1706
## for all the patients
table(mcgill.AIPS$cl[1706,])

## information of the first model
mcgill.AIPS$gs.info[1706,]

## We can do the samething using only one sample
mcgill.AIPS.first <- mclapply.AIPS (mcgill.gq$D[,1,drop=FALSE], 
                                    mcgill.gq$EntrezID)

## Compare the assignments for patient 1
table(mcgill.AIPS$cl[,1],mcgill.AIPS.first$cl[,1])

meoyo/AIPS documentation built on May 22, 2019, 6:51 p.m.