PCOPA {coGPS} | R Documentation

## P-value based outlier gene detection

### 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")

[Package coGPS version 1.36.0 Index]