uvGsa: Uni-Variate Gene Set Analysis.

In dmontaner/mdgsa: Multi Dimensional 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'.

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".

Value

A data.frame with a row for each Gene Set or block. Columns are:

N:

number of genes annotated to the Gene Set.

lor:

log Odds Ratio estimated for the Gene Set.

pval:

p-values associated to each log Odds Ratio.

padj:

adjusted p-values.

sd:

standard deviations associated to each log Odds Ratio.

t:

t statistic associated to each log Odds Ratio.

Author(s)

David Montaner [e-mail]

See Also

mdGsa, uvPat, glm.fit, p.adjust

Examples

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

dmontaner/mdgsa documentation built on May 15, 2019, 9:35 a.m.