arrayWeights {limma} | R Documentation

## Array Quality Weights

### Description

Estimates relative quality weights for each array in a multi-array experiment with replication.

### Usage

    arrayWeights(object, design = NULL, weights = NULL)

### Arguments

`object` | object of class `numeric`, `matrix`, `MAList`, `marrayNorm`, `exprSet` or `PLMset` containing log-ratios or log-values of expression for a series of microarrays.
`design` | 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.
`weights` | optional numeric matrix containing weights for each spot.

### Details

The relative reliability of each array is estimated by measuring how well the expression values for that array follow the linear model.

A joint mean and dispersion 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 a gene-by-gene manner. The final estimates of these array variances are converted to weights.

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`.

If `object` is a `PLMset`, then expression values will be taken from the slot `chip.coefs` and weights will be computed from `se.chip.coefs`. If `object` is an `exprSet`, then expression values will be taken from the `exprs` slot, but weights will not be computed.

### Value

A matrix of array weights, suitable for use in the `weights` argument of `lmFit`.

### Author(s)

Matthew Ritchie

### See Also

An overview of linear model functions in limma is given by 5.LinearModels.

### Examples

    ## Not run:
    array.wts <- arrayWeights(MA, design)
    fit.wts <- lmFit(MA, design, weights=array.wts)
    ## End(Not run)

[Package limma version 1.9.6 Index]