ssea.prepare {Mergeomics} | R Documentation

## 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.

### 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.

### 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.

### Author(s)

Ville-Petteri Makinen

### 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.

### 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")

[Package Mergeomics version 1.18.0 Index]