qualify: Probe Set Quality Control Functions

Description Usage Arguments Details Value Note Author(s) See Also Examples

Description

Converts Affymetrix probe level data to expression levels by fitting a multichip model.

Usage

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qualify(xps.data,
        filename   = character(0),
        filedir    = getwd(),
        tmpdir     = "",
        update     = FALSE,
        select     = "none",
        method     = character(),
        option     = "transcript",
        logbase    = "log2",
        exonlevel  = "",
        params     = list(),
        xps.scheme = NULL,
        add.data   = TRUE,
        verbose    = TRUE)

qualify.rlm(xps.data,
            filename   = character(0),
            filedir    = getwd(),
            tmpdir     = "",
            update     = FALSE,
            option     = "transcript",
            exonlevel  = "",
            xps.scheme = NULL,
            add.data   = TRUE,
            verbose    = TRUE)

xpsQualify(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.

select

type of probes to select for summarization.

method

qualification method to use, currently rlm.

option

option determining the grouping of probes for summarization, one of ‘transcript’, ‘exon’, ‘probeset’; exon/genome arrays only.

logbase

logarithm base as character, one of ‘0’, ‘log’, ‘log2’, ‘log10’.

exonlevel

exon annotation level determining which probes should be used for summarization; exon/genome arrays only.

params

vector of parameters for summarization method.

xps.scheme

optional alternative SchemeTreeSet.

add.data

logical. If TRUE expression data will be included as slot data.

verbose

logical, if TRUE print status information.

object

object of class DataTreeSet.

...

the arguments described above.

Details

Converts Affymetrix probe level data to expression levels by fitting a multichip model.

This function stores three types of ROOT trees in filename:
- quality trees containing expression levels, normalized unscaled standard errors (NUSE), relative log expressions (RLE)
- residual trees containing the residual SE and the model fit weights
- border trees containing the border intensities, mean border intensities and center of intensities (COI)

xpsQualify is the DataTreeSet method called by function qualify, containing the same parameters.

Value

An QualTreeSet.

Note

This function takes any DataTreeSet and computes expression levels by summarizing the probe set values into one expression measure. It does NOT do any further preprocessing such as background correction or (quantile) normalization. If you want to do background correction and/or normalization first then you need to use function fitQC.

Author(s)

Christian Stratowa

See Also

fitQC

Examples

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## Not run: 
## first, load 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 stepwise

## background correction
data.bg.rma <- bgcorrect.rma(data.test3,"tmp_Test3RMABgrd",filedir=getwd())

## normalize quantiles
data.qu.rma <- normalize.quantiles(data.bg.rma,"tmp_Test3RMANorm",filedir=getwd())

## summarize medianpolish
data.mp.rma <- summarize.rma(data.qu.rma,"tmp_Test3RMAExpr",filedir=getwd(),tmpdir="")

## qualification - rlm

## fit model on raw data
data.raw.rlm <- qualify.rlm(data.test3, "tmp_Test3RawQual", filedir=getwd(), tmpdir="", option="transcript", add.data=TRUE)

## fit model on background adjusted data
data.adj.rlm <- qualify.rlm(data.bg.rma, "tmp_Test3AdjQual", filedir=getwd(), tmpdir="", option="transcript", add.data=TRUE)

## fit model on normalized data
data.nrm.rlm <- qualify.rlm(data.qu.rma, "tmp_Test3NormQual", filedir=getwd(), tmpdir="", option="transcript", add.data=TTRUE)

## get expression levels
expr.raw.rlm <- validData(data.raw.rlm)
expr.adj.rlm <- validData(data.adj.rlm)
expr.nrm.rlm <- validData(data.nrm.rlm)

## get borders
brd.raw <- borders(data.raw.rlm)
brd.adj <- borders(data.adj.rlm)

## get residuals
res.raw <- residuals(data.raw.rlm)
res.adj <- residuals(data.adj.rlm)

## get weights
w.raw <- weights(data.raw.rlm)
w.adj <- weights(data.adj.rlm)

## End(Not run)

xps documentation built on May 2, 2018, 2:33 a.m.