f.pvalue: A function for quickly calculating f statistic p-values for...
In sva: Surrogate Variable Analysis

Description Usage Arguments Value Examples

This function does simple linear algebra to calculate f-statistics for each row of a data matrix comparing the nested models defined by the design matrices for the alternative (mod) and and null (mod0) cases. The columns of mod0 must be a subset of the columns of mod.

1	f.pvalue(dat, mod, mod0)

`dat`	The transformed data matrix with the variables in rows and samples in columns
`mod`	The model matrix being used to fit the data
`mod0`	The null model being compared when fitting the data

p A vector of F-statistic p-values one for each row of dat.

library(bladderbatch)
data(bladderdata)
dat <- bladderEset[1:50,]

pheno = pData(dat)
edata = exprs(dat)
mod = model.matrix(~as.factor(cancer), data=pheno)
mod0 = model.matrix(~1,data=pheno)

pValues = f.pvalue(edata,mod,mod0)
qValues = p.adjust(pValues,method="BH")