expFarms: Factor Analysis for Robust Microarray Summarization

Description Usage Arguments Details Value See Also Examples

View source: R/farms.R


This function converts an instance of AffyBatch into an instance of exprSet-class using a factor analysis model for which a Bayesian Maximum a Posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise.


          expFarms(object, bgcorrect.method = "none", pmcorrect.method = "pmonly", 
        normalize.method = "quantiles",  weight, mu,  weighted.mean, laplacian, robust, correction, centering, spuriousCorrelation, ...)



An instance of AffyBatch.


Hyperparameter value in the range of [0,1] which determines the influence of the prior. The default value is 0.5


the name of the background adjustment method


the name of the PM adjustment method


the normalization method to use


Hyper-parameter value which allows to quantify different aspects of potential prior knowledge. Values near zero assumes that most genes do not contain a signal, and introduces a bias for loading matrix elements near zero. Default value is 0


Boolean flag, that indicates whether a weighted mean or a least square fit is used to summarize the loading matrix. The default value is set to FALSE.


Boolean flag, indicates whether a Laplacian prior for the factor is employed or not. Default value is FALSE.


Boolean flag, that ensures non-constant results. Default value is TRUE.


Value that indicates whether the covariance matrix should be corrected for negative eigenvalues which might emerge from the non-negative correlation constraints or not. Default = O (means that no correction is done), 1 (minimal noise (0.0001) is added to the diagonal elements of the covariance matrix to force positive definiteness), 2 (Maximum Likelihood solution to compute the nearest positive definite matrix under the given non-negative correlation constraints of the covariance matrix)


Indicates whether the data is "median" or "mean" centered. Default value is "median".


Numeric value in the range of [0,1] that quantifies the suppression of spurious correlation when using the Laplacian prior. Default value is 0 (no suppression). Note, that this parameter is only active when the laplacian parameter is set to TRUE.


other arguments to be passed to expresso.


This function is a wrapper for expresso.



See Also

expresso, qFarms, lFarms.


eset <- expFarms(testAffyBatch, bgcorrect.method = "none", pmcorrect.method = "pmonly", normalize.method = "constant", weight=0.5)

Example output

Loading required package: affy
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package:BiocGenericsThe following objects are masked frompackage:parallel:

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked frompackage:stats:

    IQR, mad, sd, var, xtabs

The following objects are masked frompackage:base:

    anyDuplicated, append, as.data.frame, basename, cbind, colnames,
    dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
    grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
    rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which.max, which.min

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: MASS
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Citation: S. Hochreiter et al.,
A new summarization method for affymetrix probe level data,
Bioinformatics, 22, 8, 943-949, 2006

Citation: W. Talloen et al.,
I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data,
Bioinformatics, 23, 21, 2897-2902, 2007
BibTex: enter 'toBibtex(citation("farms"))'

Homepage: http://www.bioinf.jku.at/software/farms/farms.html

FARMS Package Version 1.42.0

Changes in FARMS:
For all changes previous to 1.3.0, see the farms vignette.
Version 1.3.0: Added I/NI-calls for filtering
               Adjusted Hyperparameters for alternative CDFs,
               probes set standardized, weighted mean
               Works now with R >= 2.8 and Bioconductor 2.3,
               Changed termination criterion, initialization values,
               factors and loadings scaled, added argument robust
               Update for R-2.11
               Updated I/NI-Call for Laplace-FARMS version,
               Maximum likelihood correlation structure given
               non-negative constraints
Version 1.4.0: Default centering changed to median
Version 1.8.x: Suppression of spurious correlation (Laplace-FARMS)

background correction: none 
normalization: constant 
PM/MM correction : pmonly 
expression values: farms 
background correcting...done.
2 ids to be processed
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farms documentation built on Nov. 8, 2020, 6:08 p.m.