genediff {LMGene} | R Documentation |
Computes two vectors of p-values per gene or probe
using gene-by-gene anova with individual gene MSE using
both the gene-specific MSE and the posterior mean MSE for
each term in the anova.
Assumes a fixed effects model and the correct denominator for all comparisons is the MSE
genediff(eS, model=NULL)
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 . |
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.
pvlist |
a list containing two sets of p-values obtained by gene specific MSE and the posterior MSE methods |
David Rocke and Geun-Cheol Lee
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/
#library library(Biobase) library(LMGene) #data data(sample.mat) data(vlist) LoggedSmpd0<-neweS(lnorm(log(sample.mat)),vlist) pvlist<-genediff(LoggedSmpd0) pvlist$Posterior[1:5,]