LMGene {LMGene}R Documentation

LMGene main function

Description

LMGene calls function genediff to calculate the raw p-values of all genes and then calls function pvadjust to calculate the adjusted p-values of all genes. Finally, calls function rowlist to list the names of genes that are selected as significant under the specified significance level.

Usage

LMGene(eS, model=NULL, level = 0.05)

Arguments

eS Array data. must be exprSet type and the log-transformation and the normalization of exprSet@exprs are recommended.
model Specifies model to be used. Default is to use all variables from eS without interactions. See details.
level Significance level

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.
level indicates False Discovery Rate, e.g. level=0.05 means 5

'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

lmres A list which contains significant gene names for each considered factor

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, pvadjust, rowlist

Examples

#library
library(Biobase)
library(LMGene)

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

siggeneslist<-LMGene(LoggedSample, 'patient + dose', 0.01)


[Package LMGene version 1.8.0 Index]