express {xps} | R Documentation

## Compute expression levels from raw data

### Description

This function allows to combine different algorithms to compute expression levels, or to return the result for different algorithms only.

### Usage

    express(xps.data,
            filename = character(),
            filedir = getwd(),
            tmpdir = "",
            update = FALSE,
          # background correction
            bgcorrect.method = NULL,
            bgcorrect.select = character(),
            bgcorrect.option = character(),
            bgcorrect.params = list(),
          # normalization
            normalize.method = NULL,
            normalize.select = character(),
            normalize.option = character(),
            normalize.logbase = character(),
            normalize.params = list(),
          # expression values
            summarize.method = NULL,
            summarize.select = character(),
            summarize.option = character(),
            summarize.logbase = character(),
            summarize.params = list(),
          # reference values
            reference.index  = 0,
            reference.method = "mean",
            reference.params = list(0),
          # misc.
            exonlevel  = "",
            xps.scheme = NULL,
            add.data   = TRUE,
            verbose    = TRUE)

    xpsPreprocess(object, ...)

### Arguments

`xps.data` | object of class `DataTreeSet`.
`filename` | file name of ROOT data file.
`filedir` | system directory where ROOT data file should be stored.
`tmpdir` | optional temporary directory where temporary ROOT files should be stored.
`update` | logical. If `TRUE` the existing ROOT data file `filename` will be updated.
`bgcorrect.method` | background method to use.
`bgcorrect.select` | type of probes to select for background correction.
`bgcorrect.option` | type of background correction to use.
`bgcorrect.params` | vector of parameters for background method.
`normalize.method` | normalization method to use.
`normalize.select` | type of probes to select for normalization.
`normalize.option` | normalization option.
`normalize.logbase` | logarithm base as character, one of ‘0’, ‘log’, ‘log2’, ‘log10’.
`normalize.params` | vector of parameters for normalization method.
`summarize.method` | summarization method to use.
`summarize.select` | type of probes to select for summarization.
`summarize.option` | option determining the grouping of probes for summarization, one of ‘transcript’, ‘exon’, ‘probeset’; exon arrays only.
`summarize.logbase` | logarithm base as character, one of ‘0’, ‘log’, ‘log2’, ‘log10’.
`summarize.params` | vector of parameters for summarization method.
`reference.index` | index of reference tree to use, or 0.
`reference.method` | for `refindex=0`, either trimmed mean or median of trees.
`reference.params` | vector of parameters for reference method.
`exonlevel` | exon annotation level determining which probes should be used for summarization; exon/genome arrays only.
`xps.scheme` | optional alternative `SchemeSet`.
`add.data` | logical. If `TRUE` expression data will be included as slot `data`.
`verbose` | logical, if `TRUE` print status information.
`object` | object of class `DataSet`.
`...` | the arguments described above.

### Details

This function allows to combine different algorithms to compute expression levels, or to return the result for different algorithms only.

`xpsPreprocess` is the `DataSet` method called by function `express`, containing the same parameters.

### Value

An object of type `DataTreeSet` or `ExprTreeSet`.

### Author(s)

Christian Stratowa

### See Also

`bgcorrect`, `normalize`, `summarize`

### Examples

    ## load existing ROOT scheme file and ROOT data file
    scheme.test3 <- root.scheme(paste(.path.package("xps"),"schemes/SchemeTest3.root",sep="/"))
    data.test3 <- root.data(scheme.test3, paste(.path.package("xps"),"rootdata/DataTest3_cel.root",sep="/"))

    ## compute rma with a single call to express()
    expr.rma <- express(data.test3,"tmp_Test3Exprs",filedir=getwd(),tmpdir="",update=FALSE,
                bgcorrect.method="rma",bgcorrect.select="none",bgcorrect.option="pmonly:epanechnikov",bgcorrect.params=c(16384),
                normalize.method="quantile",normalize.select="pmonly",normalize.option="transcript:together:none",normalize.logbase="0",normalize.params=c(0.0),
                summarize.method="medianpolish",summarize.select="pmonly",summarize.option="transcript",summarize.logbase="log2",summarize.params=c(10, 0.01, 1.0),
                verbose=FALSE)

    ## get expression data.frame
    expr <- exprs(expr.rma)
    head(expr)

    ## plot expression levels
    if (interactive()) {
    boxplot(expr.rma)
    boxplot(log2(expr[,3:6]))
    }

    ## Not run:
    ## examples using Affymetrix human tissue dataset (see also xps/examples/script4exon.R)

    ## example - exon array, e.g. HuEx-1_0-st-v2:
    scmdir <- "/Volumes/GigaDrive/CRAN/Workspaces/Schemes"
    datdir <- "/Volumes/GigaDrive/CRAN/Workspaces/ROOTData"
    scheme.exon <- root.scheme(paste(scmdir,"Scheme_HuEx10stv2r2_na25.root",sep="/"))
    data.exon   <- root.data(scheme.exon, paste(datdir,"HuTissuesExon_cel.root",sep="/"))

    workdir <- "/Volumes/GigaDrive/CRAN/Workspaces/Exon/hutissues/exon"
    expr.rma <- express(data.exon,"HuExonExprs",filedir=workdir,tmpdir="",update=F,
                bgcorrect.method="rma",bgcorrect.select="antigenomic",bgcorrect.option="pmonly:epanechnikov",bgcorrect.params=c(16384),
                normalize.method="quantile",normalize.select="pmonly",normalize.option="transcript:together:none",normalize.logbase="0",normalize.params=c(0.0),
                summarize.method="medianpolish",summarize.select="pmonly",summarize.option="transcript",summarize.logbase="log2",summarize.params=c(10, 0.01, 1.0),
                exonlevel="metacore+affx")
    ## End(Not run)

[Package xps version 1.4.10 Index]