avearrays: Average Over Replicate Arrays

In hdeberg/limma: Linear Models for Microarray Data

Description

Condense a microarray data object so that technical replicate arrays are replaced with (weighted) averages.

Usage

## Default S3 method:
avearrays(x, ID=colnames(x), weights=NULL)
## S3 method for class 'MAList'
avearrays(x, ID=colnames(x), weights=x$weights)
## S3 method for class 'EList'
avearrays(x, ID=colnames(x), weights=x$weights)

Arguments

x	a matrix-like object, usually a matrix, MAList or EList object.
ID	sample identifier.
weights	numeric matrix of non-negative weights

Details

A new data object is computed in which technical replicate arrays are replaced by their (weighted) averages.

For an MAList object, the components M and A are both averaged in this way, as are weights and any matrices found in object$other.

EList objects are similar, except that the E component is averaged instead of M and A.

If x is of mode "character", then the replicate values are assumed to be equal and the first is taken as the average.

Value

A data object of the same class as x with a column for each unique value of ID.

Author(s)

Gordon Smyth

See Also

avereps.

02.Classes gives an overview of data classes used in LIMMA.

Examples

x <- matrix(rnorm(8*3),8,3)
colnames(x) <- c("a","a","b")
avearrays(x)

hdeberg/limma documentation built on Dec. 20, 2021, 3:43 p.m.