| MArrayLM-class {limma} | R Documentation |
A list-based class for storing the results of fitting gene-wise linear models to a batch of microarrays.
Objects are normally created by lmFit.
MArrayLM objects do not contain any slots (apart from .Data) but they should contain the following list components:
coefficients:matrix containing fitted coefficients or contrastsstdev.unscaled:matrix containing unscaled standard deviations of the coefficients or contrastssigma:numeric vector containing residual standard deviations for each genedf.residual:numeric vector containing residual degrees of freedom for each geneObjects may also contain the following optional components:
Amean:numeric vector containing the average log-intensity for each probe over all the arrays in the original linear model fit.
Note this vector does not change when a contrast is applied to the fit using contrasts.fit.genes:data.frame containing gene names and annotationdesign:matrix of full column rankcontrasts:matrix defining contrasts of coefficients for which results are desiredF:numeric vector giving moderated F-statistics for testing all contrasts equal to zeroF.p.value:numeric vector giving p-value corresponding to F.stats2.prior:numeric value giving empirical Bayes estimated prior value for residual variancesdf.prior:numeric vector giving empirical Bayes estimated degrees of freedom associated with s2.prior for each genes2.post:numeric vector giving posterior residual variancest:matrix containing empirical Bayes t-statisticsvar.prior:numeric vector giving empirical Bayes estimated prior variance for each true coefficientcov.coefficients:matrix giving the unscaled covariance matrix of the estimable coefficientspivot:integer vector giving the order of coefficients in cov.coefficients. Is computed by the QR-decomposition of the design matrix.
If there are no weights and no missing values, then the MArrayLM objects returned by lmFit will also contain the QR-decomposition of the design matrix, and any other components returned by lm.fit.
RGList objects will return dimensions and hence functions such as dim, nrow and ncol are defined.
MArrayLM objects inherit a show method from the virtual class LargeDataObject.
The functions ebayes and classifyTestsF accept MArrayLM objects as arguments.
Gordon Smyth
02.Classes gives an overview of all the classes defined by this package.