uvGsa: Uni-Variate Gene Set Analysis.

Description

Performs a Uni-Variate Gene Set Analysis using a logistic regression model.

Usage

uvGsa(index, annot, p.adjust.method = "BY", family = quasibinomial(),
  verbose = TRUE, verbosity = 100, fulltable = FALSE, ...)

Arguments

index

ranking index, generally a numerical named vector.

annot

an annotation list.

p.adjust.method

p-value adjustment method for multiple testing.

family

see glm.fit.

verbose

verbose.

verbosity

integer indicating which iterations should be indicated if verbose = TRUE.

fulltable

if TRUE, 'sd', 't' and 'convergence' indicator from the glm fit are included in the output.

...

further arguments to be pasted to glm.fit, for instance 'weights'.

Value

A data.frame with a row for each Gene Set or block. Columns are: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Details

'index' may also be a numerical matrix or data.frame. If such a matrix has more than one column, the ranking index is taken form the first one. The remaining columns are used as covariates to correct for within the analysis.

Default p-value correction is "BY".

Examples

Run this code

rindex <- rnorm (1000)
names (rindex) <- paste0 ("gen", 1:1000)

annotList <- list (geneSet1 = sample (names (rindex), size = 10),
                   geneSet2 = sample (names (rindex), size = 15),
                   geneSet3 = sample (names (rindex), size = 20))

res <- uvGsa (rindex, annotList)
res