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\name{ssea.finish}
\alias{ssea.finish}
\title{
Organize and save MSEA results
}
\description{
\code{ssea.finish} organizes and stores the MSEA results into relevant
output files.
}
\usage{
ssea.finish(job)
}
\arguments{
\item{job}{
data list including the results of MSEA process. \code{job} will be
saved after getting organized: \preformatted{
label: unique identifier for the analysis.
folder: output folder for results.
resultsdata: frame including indexed module identities
(MODULE) and enrichment P-values (P).
database: database including indexed identities for
modules, genes, and markers.
}
}
}
\details{
\code{ssea.finish} obtains module statistics (member genes, size, length,
density, enrichment scores, false discovery rates), finds the top marker
within genes, updates the gene scores and gene sizes (i.e. number of markers
for each gene), and saves the organized results regarding the modules and
genes into the relevant files.
}
\value{
\item{job }{data list including the organized results of MSEA process:
\preformatted{
results: updated information of modules:
number of distinct member genes (NGENES),
number of distinct member markers (NLOCI),
ratio of distinct to non-distinct markers (DENSITY),
false discovery rates (FDR).
generesults: updated gene-specific information including:
indexed gene identity (GENE),
gene size (NLOCI),
unadjusted enrichment score (SCORE),
marker with maximum value (LOCUS),
marker value (VALUE).
}
}
}
\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)
job.msea <- ssea.control(job.msea)
job.msea <- ssea.analyze(job.msea)
job.msea <- ssea.finish(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")
}
\references{
Shu L, Zhao Y, Kurt Z, Byars SG, Tukiainen T, Kettunen J, Orozco LD,
Pellegrini M, Lusis AJ, Ripatti S, Zhang B, Inouye M, Makinen V-P, Yang X.
Mergeomics: multidimensional data integration to identify pathogenic
perturbations to biological systems. BMC genomics. 2016;17(1):874.
}
\author{
Ville-Petteri Makinen
}
\seealso{
\code{\link{ssea.analyze}}, \code{\link{ssea.control}},
\code{\link{ssea.prepare}}, \code{\link{ssea.start}},
\code{\link{ssea2kda}}
}
|
