Package 'limma' - Bioconductor

18 arrayWeights
Arguments
object
design
weights
method
maxiter
tol
maxratio
trace
object of class numeric, matrix, MAList, marrayNorm, ExpressionSet or PLMset
containing log-ratios or log-values of expression for a series of microarrays.
the design matrix of the microarray experiment, with rows corresponding to
arrays and columns to coefficients to be estimated. Defaults to the unit vector
meaning that the arrays are treated as replicates.
optional numeric matrix containing prior weights for each spot.
character string specifying the estimating algorithm to be used. Choices are
"genebygene" and "reml".
maximum number of iterations allowed.
convergence tolerance.
maximum ratio between largest and smallest weights before iteration stops
logical variable. If true then output diagnostic information at each iteration of
the ’"reml"’ algorithm, or at every 1000th iteration of the ’"genebygene"’ algorithm.
Details
Value
The relative reliability of each array is estimated by measuring how well the expression values for
that array follow the linear model.
The method is described in Ritchie et al (2006). A heteroscedastic model is fitted to the expression
values for each gene by calling the function lm.wfit. The dispersion model is fitted to the squared
residuals from the mean fit, and is set up to have array specific coefficients, which are updated in
either full REML scoring iterations, or using an efficient gene-by-gene update algorithm. The final
estimates of these array variances are converted to weights.
The data object object is interpreted as for lmFit. In particular, the arguments design and
weights will be extracted from the data object if available and do not normally need to be set
explicitly in the call; if any of these are set in the call then they will over-ride the slots or components
in the data object.
arrayWeightsSimple is a fast version of arrayWeights with method="reml", no prior weights
and no missing values.
A vector of array weights.
Author(s)
Matthew Ritchie and Gordon Smyth
References
Ritchie, M. E., Diyagama, D., Neilson, van Laar, R., J., Dobrovic, A., Holloway, A., and Smyth, G.
K. (2006). Empirical array quality weights in the analysis of microarray data. BMC Bioinformatics
7, 261. http://www.biomedcentral.com/1471-2105/7/261/abstract