limma (version 3.28.14)

02.Classes: Topic: Classes Defined by this Package

Description

This package defines the following data classes.

RGList

A class used to store raw intensities as they are read in from an image analysis output file, usually by read.maimages.

MAList

Intensities converted to M-values and A-values, i.e., to with-spot and whole-spot contrasts on the log-scale. Usually created from an RGList using MA.RG or normalizeWithinArrays. Objects of this class contain one row for each spot. There may be more than one spot and therefore more than one row for each probe.

EListRaw

A class to store raw intensities for one-channel microarray data. May or may not be background corrected. Usually created by read.maimages.

EList

A class to store normalized log2 expression values for one-channel microarray data. Usually created by normalizeBetweenArrays.

MArrayLM

Store the result of fitting gene-wise linear models to the normalized intensities or log-ratios. Usually created by lmFit. Objects of this class normally contain only one row for each unique probe.

TestResults

Store the results of testing a set of contrasts equal to zero for each probe. Usually created by decideTests. Objects of this class normally contain one row for each unique probe.

All these data classes obey many analogies with matrices. In the case of RGList, MAList, EListRaw and EList, rows correspond to spots or probes and columns to arrays. In the case of MarrayLM, rows correspond to unique probes and the columns to parameters or contrasts. The functions summary, dim, length, ncol, nrow, dimnames, rownames, colnames have methods for these classes. Objects of any of these classes may be subsetted. Multiple data objects may be combined by rows (to add extra probes) or by columns (to add extra arrays).

Furthermore all of these classes may be coerced to actually be of class matrix using as.matrix, although this entails loss of information. Fitted model objects of class MArrayLM can be coerced to class data.frame using as.data.frame.

The first three classes belong to the virtual class LargeDataObject. A show method is defined for LargeDataOjects which uses the utility function printHead.

See Also

01.Introduction, 02.Classes, 03.ReadingData, 04.Background, 05.Normalization, 06.LinearModels, 07.SingleChannel, 08.Tests, 09.Diagnostics, 10.GeneSetTests, 11.RNAseq