qualify: Probe Set Quality Control Functions

Description

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

Usage

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.

Value

An QualTreeSet.

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.

Examples

Run this code

## 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)