PCOPA: P-value based outlier gene detection

In coGPS: cancer outlier Gene Profile Sets

Description

Calculate P-value based statistics for outlier gene detection in dataset merged from multiple studies and give out outlier gene list for each patient.

Usage

PCOPA(exprslist, alpha, side, type)

Arguments

exprslist	Each element of exprslist is a list with the first element being exprs and the second element being classlab. Each row of exprs represents one gene and each column represents one sample. classlab is a zero-one vector indicating the status of samples. We use 0 for the baseline group, usually the normal group, and 1 for the comparison group, usually the tumor group.
alpha	Significance level for P-value.
side	A vector specifying the definition of P-value in each of the study, which could be either up, down, or twosided.
type	A vector specifying whether the outlier pattern is subtype or uniform.

Value

PCOPAstatistics	the P-value based outlier gene detection statistics
outliergene_bypatient	a list whose length equals the number of tumor samples (patients). each element of the list is a list of length equaling to the length of exprslist, in other words the number of studies(or data type), showing the outlier gene for each patient in each study (or data type)

Author(s)

Yingying Wei

References

Wei, Y., Hennessey, P., Gaykalova, D., Califano, J.A., Ochs, M.F., (2011) Cancer Outlier Gene Profile Sets Elucidate Pathways in Head and Neck Squamous Cell Carcinoma.

Examples

#read in data
data(Exon_exprs_matched)
data(Methy_exprs_matched)
data(CNV_exprs_matched)
data(Exon_classlab_matched)
data(Methy_classlab_matched)
data(CNV_classlab_matched)
head(Exon_exprs_matched)

#exprslist[[i]]$exprs should be in matrix format
Exon_exprs<-as.matrix(Exon_exprs_matched)
Methy_exprs<-as.matrix(Methy_exprs_matched)
CNV_exprs<-as.matrix(CNV_exprs_matched)

#exprslist[[i]]$classlab should be in vector format
Exon_classlab<-unlist(Exon_classlab_matched)
Methy_classlab<-unlist(Methy_classlab_matched)
CNV_classlab<-unlist(CNV_classlab_matched)

#make an exprslist consisting 3 studies
trylist<-list()
trylist[[1]]<-list(exprs=Exon_exprs,classlab=Exon_classlab)
trylist[[2]]<-list(exprs=Methy_exprs,classlab=Methy_classlab)
trylist[[3]]<-list(exprs=CNV_exprs,classlab=CNV_classlab)

#calculate P-value based statistics for outlier gene detection and output the outlier gene list for each patient
a7<-PCOPA(trylist,0.05,side=c("up","down","up"),type="subtype")

coGPS documentation built on Nov. 8, 2020, 11:11 p.m.