Mergeomics (version 1.0.0)

ssea.prepare: Prepare an indexed database for MSEA

Description

ssea.prepare prepares a database that includes hierarchical for modules, i.e. it collects gene list and unique marker list of the modules for MSEA process

Usage

ssea.prepare(job)

Arguments

job

a data list with the following components:

modules: module identities as characters.
genesgene: identities as characters.
loci: marker identities as characters.
moddata: preprocessed module data (indexed identities).
gendata: preprocessed mapping data (indexed identities).
locdata: preprocessed marker data (indexed identities).
mingenes: minimum module size allowed.
maxgenes: maximum module size allowed.
maxoverlap: maximum module overlap allowed (1.0 to skip).
quantiles: quantile points for test statistic.

Value

job

an updated data list with the following components:

modules: finalized module names.
moddata: finalized module data.
gendata: finalized mapping data.
locdata: finalized marker data.
quantiles: verified quantile points.
database$modulesizes: gene counts for modules.
database$modulelengths: distinct markers counts for
modules.
database$moduledensities: ratio between distinct and
non-distinct markers.
database$genesizeslocus: count for each gene.
database$module2genes: gene lists for each module.
database$gene2locilocus: lists for each gene.
database$locus2row: indices in the marker data frame
for each marker.
database$observed: matrix of observed counts of values
that exceed each quantile point for each marker.
database$expected: 1.0 - quantile points.

Details

ssea.prepare removes extreme-sized modules, constructs a hierarchical representation of genes and modules, obtains hit counts for markers, and returns the finalized module, genes, markers, database information.

References

Shu L, Zhao Y, Kurt Z, Byars S, Tukiainen T, Kettunen J, Ripatti S, Zhang B, Inouye M, Makinen VP, Yang X. Mergeomics: integration of diverse genomics resources to identify pathogenic perturbations to biological systems. bioRxiv doi: http://dx.doi.org/10.1101/036012

See Also

ssea.analyze, ssea.control, ssea.finish, ssea.start, ssea2kda

Examples

job.msea <- list()
job.msea$label <- "hdlc"
job.msea$folder <- "Results"
job.msea$genfile <- system.file("extdata", 
"genes.hdlc_040kb_ld70.human_eliminated.txt", package="Mergeomics")
job.msea$marfile <- system.file("extdata", 
"marker.hdlc_040kb_ld70.human_eliminated.txt", package="Mergeomics")
job.msea$modfile <- system.file("extdata", 
"modules.mousecoexpr.liver.human.txt", package="Mergeomics")
job.msea$inffile <- system.file("extdata", 
"coexpr.info.txt", package="Mergeomics")
job.msea$nperm <- 100 ## default value is 20000

## ssea.start() process takes long time while merging the genes sharing high
## amounts of markers (e.g. loci). it is performed with full module list in
## the vignettes. Here, we used a very subset of the module list (1st 10 mods
## from the original module file) and we collected the corresponding genes
## and markers belonging to these modules:
moddata <- tool.read(job.msea$modfile)
gendata <- tool.read(job.msea$genfile)
mardata <- tool.read(job.msea$marfile)
mod.names <- unique(moddata$MODULE)[1:min(length(unique(moddata$MODULE)),
10)]
moddata <- moddata[which(!is.na(match(moddata$MODULE, mod.names))),]
gendata <- gendata[which(!is.na(match(gendata$GENE, 
unique(moddata$GENE)))),]
mardata <- mardata[which(!is.na(match(mardata$MARKER, 
unique(gendata$MARKER)))),]

## save this to a temporary file and set its path as new job.msea$modfile:
tool.save(moddata, "subsetof.coexpr.modules.txt")
tool.save(gendata, "subsetof.genfile.txt")
tool.save(mardata, "subsetof.marfile.txt")
job.msea$modfile <- "subsetof.coexpr.modules.txt"
job.msea$genfile <- "subsetof.genfile.txt"
job.msea$marfile <- "subsetof.marfile.txt"
## run ssea.start() and prepare for this small set: (due to the huge runtime)
job.msea <- ssea.start(job.msea)
job.msea <- ssea.prepare(job.msea)

## Remove the temporary files used for the test:
file.remove("subsetof.coexpr.modules.txt")
file.remove("subsetof.genfile.txt")
file.remove("subsetof.marfile.txt")