rowaov {LMGene}R Documentation

Gene by gene anova functioin

Description

Computes the mean squares and degrees of freedom for gene-by-gene anovas.

Usage

rowaov(eS, model=NULL)

Arguments

eS Array data. must be a exprSet type and the log-transformation and the normalization of exprSet@exprs are recommended
model Model used for comparison. See details and LMGene.

Details

The input argument, eS, must be exprSet type from Biobase package. If you have a matrix data and information about the considered factors, then you can use neweS to conver the data into exprSet. Please see neweS in more detail.

'model' is an optional character string, constructed like the right-hand side of a formula for lm. It specifies which of the variables in the exprSet will be used in the model and whether interaction terms will be included. If model=NULL, it uses all variables from the exprSet without interactions. Be careful of using interaction terms with factors: this often leads to overfitting, which will yield an error.

Value

resmat A matrix of MSE and DF of all factors for all genes

Author(s)

David Rocke and Geun-Cheol Lee

References

David M. Rocke (2004), Design and analysis of experiments with high throughput biological assay data, Seminars in Cell & Developmental Biology, 15, 703-713.

http://www.idav.ucdavis.edu/~dmrocke/

See Also

genediff, mlm2lm

Examples

#library
library(Biobase)
library(LMGene)

#data
data(sample.mat)
data(vlist)
LoggedSmpd0<-neweS(lnorm(log(sample.mat)),vlist)

resmat <- rowaov(LoggedSmpd0)
resmat[,1:3]

[Package LMGene version 1.8.0 Index]