MArrayLM-class {limma} | R Documentation

## Microarray Linear Model Fit - class

### Description

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`.

### Slots/Components

`MArrayLM` objects do not contain any slots (apart from `.Data`) but they should contain the following list components:

`coefficients`:
  `matrix` containing fitted coefficients or contrasts
`stdev.unscaled`:
  `matrix` containing unscaled standard deviations of the coefficients or contrasts
`sigma`:
  `numeric` vector containing residual variances for each gene
`df.residual`:
  `numeric` vector containing residual degrees of freedom for each gene

Object may also contain the following optional components:

`genes`:
  `data.frame` containing gene names and annotation
`design`:
  design `matrix` of full column rank
`contrasts`:
  `matrix` defining contrasts of coefficients for which results are desired
`s2.prior`:
  `numeric` value giving empirical Bayes estimated prior value for residual variances
`df.prior`:
  `numeric` vector giving empirical Bayes estimated degrees of freedom associated with `s2.prior` for each gene
`s2.post`:
  `numeric` vector giving posterior residual variances
`t`:
  `matrix` containing empirical Bayes t-statistics
`var.prior`:
  `numeric` vector giving empirical Bayes estimated variance for each true coefficient

### Methods

`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 `classifyTests` accept `MArrayLM` objects as arguments.

### Author(s)

Gordon Smyth

### See Also

2.Classes gives an overview of all the classes defined by this package.

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