writeBedTrack {JunctionSeq} | R Documentation

## Write splice junction browser tracks

### Description

This function saves the JunctionSeq results in the form of a set of "bed" files designed for use with the UCSC genome browser.

### Usage

    writeExprBedTrack(file, jscs,
         trackLine,
         only.with.sig.gene = FALSE,
         only.sig = FALSE,
         only.testable = TRUE,
         plot.exons = TRUE, plot.junctions = TRUE, plot.novel.junctions = TRUE,
         group.RGB,
         use.score = FALSE,
         FDR.threshold = 0.05,
         count.digits = 1,
         includeGeneID = FALSE,
         includeLocusID = TRUE,
         includeGroupID = TRUE,
         output.format = c("BED", "GTF", "GFF3"),
         use.gzip = TRUE,
         verbose = TRUE)

    writeSigBedTrack(file,
         jscs,
         trackLine,
         only.sig = TRUE,
         only.testable = TRUE,
         plot.exons = TRUE, plot.junctions = TRUE, plot.novel.junctions = TRUE,
         sig.RGB = "255,0,0",
         nonsig.RGB = "0,0,0",
         use.score = TRUE,
         FDR.threshold = 0.05,
         pval.digits = 4,
         includeGeneID = FALSE,
         includeLocusID = TRUE,
         output.format = c("BED", "GTF", "GFF3"),
         use.gzip = TRUE,
         verbose = TRUE)

### Arguments

`file` | Character string. File path for the output bed file.
`jscs` | A `JunctionSeqCountSet`. Usually created by `runJunctionSeqAnalyses`. Alternatively, this can be created manually by `readJunctionSeqCounts`. However in this case a number of additional steps will be necessary: Dispersions and size factors must then be set, usually using functions `estimateSizeFactors` and `estimateJunctionSeqDispersions`. Hypothesis tests must be performed by `testForDiffUsage`. Effect sizes and parameter estimates must be created via `estimateEffectSizes`.
`trackLine` | The "track line" of the bed file. In other words, the first line of the file. By default JunctionSeq will attempt to automatically generate a reasonable track line.
`only.with.sig.gene` | Logical. If `TRUE`, only genes containing statistically significant results will be included.
`only.sig` | Logical. If `TRUE`, only statistically significant loci will be included.
`only.testable` | Logical. If `TRUE`, only loci with sufficiently high expression to be tested will be included.
`plot.exons` | Logical. If `TRUE`, exons will be plotted.
`plot.junctions` | Logical. If `TRUE`, splice junctions will be plotted.
`plot.novel.junctions` | Logical. If `TRUE`, novel splice junctions will be plotted (if plot.junctions is also `TRUE`).
`sig.RGB` | Character string. The RGB color for significant genes. Must be in the format "r,g,b", with each value ranging from 0 to 255.
`nonsig.RGB` | Character string. The RGB color for non-significant loci. Must be in the format "r,g,b", with each value ranging from 0 to 255.
`group.RGB` | Character string. The RGB color used for each experimental group. Must be in the format "r,g,b", with each value ranging from 0 to 255. Must have a length equal to the number of experimental condition values.
`use.score` | Logical. If TRUE, score each locus based on the p-value.
`FDR.threshold` | Numeric. The FDR-adjusted p-value threshold to use to assign statistical significance.
`count.digits` | Numeric. The number of digits after the decimal point to include for the mean normalized counts.
`pval.digits` | Numeric. The number of digits after the decimal point to include for the p-values.
`includeGeneID` | Logical. If TRUE, include the ID of the gene in the "name" field of each line.
`includeLocusID` | Logical. If TRUE, include the ID of the locus in the "name" field of each line.
`includeGroupID` | Logical. If TRUE, include the ID of the group in the "name" field of each line.
`output.format` | Character string. The format to use.
`use.gzip` | Logical. Whether or not to gzip the bed file.
`verbose` | Logical. if TRUE, output debugging/progress information.

### Value

This is a side-effecting function, and does not return a value.

### Examples

    data(exampleDataSet,package="JctSeqData");
    writeExprBedTrack("test.exonCoverage.bed.gz", jscs,
                      plot.exons = TRUE, plot.junctions = FALSE)

    ## Not run:
    ########################################
    #Set up example data:
    decoder.file <- system.file(
                      "extdata/annoFiles/decoder.bySample.txt",
                      package="JctSeqData");
    decoder <- read.table(decoder.file,
                      header=TRUE,
                      stringsAsFactors=FALSE);
    gff.file <- system.file(
                "extdata/cts/withNovel.forJunctionSeq.gff.gz",
                package="JctSeqData");
    countFiles <- system.file(paste0("extdata/cts/",
         decoder$sample.ID,
         "/QC.spliceJunctionAndExonCounts.withNovel.forJunctionSeq.txt.gz"),
         package="JctSeqData");
    ######################
    #Run example analysis:
    jscs <- runJunctionSeqAnalyses(sample.files = countFiles,
               sample.names = decoder$sample.ID,
               condition=factor(decoder$group.ID),
               flat.gff.file = gff.file,
               analysis.type = "junctionsAndExons"
    );
    ########################################

    #Exon coverage:
    writeExprBedTrack("test.exonCoverage.bed.gz", jscs,
                      plot.exons = TRUE, plot.junctions = FALSE)
    #Junction coverage:
    writeExprBedTrack("test.jctCoverage.bed.gz", jscs,
                      plot.exons = FALSE, plot.junctions = TRUE)
    #Both Exon and Junction coverage:
    writeExprBedTrack("test.featureCoverage.bed.gz", jscs)

    #p-values of significant features:
    writeSigBedTrack("test.pvals.bed.gz", jscs)

    ## End(Not run)

[Package JunctionSeq version 1.10.0 Index]