farms: Factor Analysis for Robust Microarray Summarization...

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

Description

This function converts a DataTreeSet into an ExprTreeSet using the Factor Analysis for Robust Microarray Summarization (FARMS) method.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
farms(xps.data,
      filename   = character(0),
      filedir    = getwd(),
      tmpdir     = "",
      normalize  = TRUE,
      weight     = 0.5,
      mu         = 0.0,
      scale      = 1.0,
      tol        = 0.00001,
      cyc        = 100,
      weighted   = TRUE,
      version    = "1.3.1",
      option     = "transcript",
      exonlevel  = "",
      xps.scheme = NULL,
      add.data   = TRUE,
      verbose    = TRUE)

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.

normalize

logical. If TRUE normalize data using quantile normalization.

weight

hyperparameter, usually set to 0.5 for version="1.3.1" and to 8.0 for version="1.3.0".

mu

hyperparameter allowing to correct for potential bias.

scale

scaling parameter, usually set to 1.0 for version="1.3.1" and to 2.0 for version="1.3.0".

tol

termination tolerance for EM algorithm.

cyc

maximum number of cycles of EM algorithm.

weighted

logical, used only with version="1.3.1". Default is TRUE.

version

version of original farms package. Currently, version="1.3.1" and version="1.3.0" are implemented. Default is version="1.3.1".

option

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

exonlevel

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

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.

Details

This function computes the FARMS (Factor Analysis for Robust Microarray Summarization) expression measure described in Hochreiter et al. for both expression arrays and exon arrays.

Parameter version currently allows the user to choose between the original implementation of FARMS as implemented in package ‘farms_1.3.0’ or enhanced FARMS as implemented in package ‘farms_1.3.1’. By default version="1.3.1" is used.

Parameter weight is a hyperparameter which determines the influence of the prior. For version="1.3.1" the value in the range of [0,1].

Parameter mu is a hyperparameter which allows to quantify different aspects of potential prior knowledge. Values near zero assume that most genes do not contain a signal and introduce a bias for loading matrix elements near zero.

Parameter weighted is a logical and indicates whether a weighted mean or a least square fit is used to summarize the loading matrix. It is applicable only to version="1.3.1".

For exon arrays it is necessary to supply the requested option and exonlevel.

Following options are valid for exon arrays:

transcript: expression levels are computed for transcript clusters, i.e. probe sets containing the same 'transcript_cluster_id'.
exon: expression levels are computed for exon clusters, i.e. probe sets containing the same 'exon_id', where each exon cluster consists of one or more probesets.
probeset: expression levels are computed for individual probe sets, i.e. for each 'probeset_id'.

Following exonlevel annotations are valid for exon arrays:

core: probesets supported by RefSeq and full-length GenBank transcripts.
metacore: core meta-probesets.
extended: probesets with other cDNA support.
metaextended: extended meta-probesets.
full: probesets supported by gene predictions only.
metafull: full meta-probesets.
affx: standard AFFX controls.
all: combination of above (including affx).

Following exonlevel annotations are valid for whole genome arrays:

core: probesets with category 'unique', 'similar' and 'mixed'.
metacore: probesets with category 'unique' only.
affx: standard AFFX controls.
all: combination of above (including affx).

Exon levels can also be combined, with following combinations being most useful:

exonlevel="metacore+affy": core meta-probesets plus AFFX controls
exonlevel="core+extended": probesets with cDNA support
exonlevel="core+extended+full": supported plus predicted probesets

Exon level annotations are described in the Affymetrix whitepaper exon_probeset_trans_clust_whitepaper.pdf:
“Exon Probeset Annotations and Transcript Cluster Groupings”.

In order to use an alternative SchemeTreeSet set the corresponding SchemeSet xps.scheme.

Value

An ExprTreeSet

Note

The expression measure obtained with FARMS is given in linear scale, analogously to the expression measures computed with mas5 and rma.

For the analysis of many exon arrays it may be better to define a tmpdir, since this will store only the results in the main file and not e.g. background and normalized intensities, and thus will reduce the file size of the main file. For quantile normalization memory should not be an issue, however DFW depends on RAM unless you are using a temporary file.

Author(s)

Christian Stratowa

References

Hochreiter, S., Clevert D.-A., and Obermayer, K. (2006), A new summarization method for Affymetrix probe level data. Bioinformatics 22(8):943-949

See Also

express

Examples

1
2
3
4
5
6
7
8
9
## 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="/"))

data.farms <- farms(data.test3,"tmp_Test3FARMS",verbose=FALSE)

## get data.frame
expr.farms <- validData(data.farms)
head(expr.farms)

xps documentation built on Nov. 8, 2020, 6 p.m.