gageComp: Compare multiple GAGE analyses results

In gage: Generally Applicable Gene-set Enrichment for Pathway Analysis

Description

This function is used to compare the results after running multiple rounds of GAGE analysis. It is frequently used after batch analysis using gagePipe, but may also be used after multiple runs of gage manually.

Usage

gageComp(sampnames, dataname, gsname = c("kegg.gs", "go.gs"), use.cols =
c("stat.mean", "q.val"), q.cutoff = 0.1, do.plot = TRUE)

Arguments

sampnames	character vector, the names of the sample groups, on which the GAGE analysis has been done and to be compared. This same argument is used in gagePipe function. These sampnames have been used to label gage result objects.
dataname	character, the name of the data on which the GAGE analysis has been done. This same argument is used in gagePipe function. This name has be included as the prefix of the GAGE analysis output file names, and will be used in the comparison output file names.
gsname	character, the name(s) of the gene set collection(s) to be considered in the comparison. In other words, this argument specifies GAGE analysis results with what type(s) of gene sets are to be compared on. Default to be c("kegg.gs", "go.gs").
use.cols	character, what columns in the gage analysis result objects will be used in the comparison. Default to be "stat.mean" (mean of gene set test statistics) and "q.val" (q-value using BH procedure). Check help information for gage function for more details on the result columns.
q.cutoff	numeric, q-value cutoff between 0 and 1 for signficant gene sets selection. Default to be 0.1. The same argument is used in gagePipe function.
do.plot	boolean, whether to plot the venn diagram for the comparison results. Default to be TRUE.

Details

gageComp works with the results of gagePipe run by default. Try to load the .RData file named after dataname first. It there is no such file, it assumes that the gage result objects have been loaded and exist in the global environment.

For the GAGE analysis results with each gene set collection specified in gsname, gagePipe compares the signficant gene set lists between the sample groups specified in sampnames. For each gene set collection, three comparisons will be done, on the 2-direction perturbed, up-regulated, and down-regulated gene sets.

The comparison results are output as tab-delimited text files. Venn digrams are only plot for comparison between 2-3 parties. But the text file outputs are not limited by the number of parties under comparison. The venn diagram is generated by calling a revised function based on the VennDigram function from limma package.

Value

The function returns invisible 1 when successfully executed.

Author(s)

Weijun Luo <[e-mail]>

References

Luo, W., Friedman, M., Shedden K., Hankenson, K. and Woolf, P GAGE: Generally Applicable Gene Set Enrichment for Pathways Analysis. BMC Bioinformatics 2009, 10:161

See Also

gagePipe pipeline for multiple GAGE analysis in a batch; gage the main function for GAGE analysis

Examples

data(gse16873)
cn=colnames(gse16873)
hn=grep('HN',cn, ignore.case =TRUE)
dcis=grep('DCIS',cn, ignore.case =TRUE)
data(kegg.gs)

library(gageData)
data(gse16873.2)
cn2=colnames(gse16873.2)
hn2=grep('HN',cn2, ignore.case =TRUE)
dcis2=grep('DCIS',cn2, ignore.case =TRUE)

#multiple GAGE analysis in a batch with the combined data
gse16873=cbind(gse16873, gse16873.2)
dataname='gse16873' #output data prefix
sampnames=c('dcis.1', 'dcis.2')
refList=list(hn, hn2+12)
sampList=list(dcis, dcis2+12)
gagePipe(gse16873, gsname = "kegg.gs", dataname = "gse16873",
    sampnames = sampnames, ref.list = refList, samp.list = sampList,
    comp.list = "paired")

#follow up comparison between the analyses
load('gse16873.gage.RData')
#list gage result objects
objects(pat = "[.]p$")
gageComp(sampnames, dataname, gsname = "kegg.gs",
    do.plot = TRUE)

Example output

[1] "dcis.1.kegg.gs.2d.p" "dcis.1.kegg.gs.p"    "dcis.2.kegg.gs.2d.p"
[4] "dcis.2.kegg.gs.p"   

gage documentation built on Dec. 13, 2020, 2:01 a.m.