uvGsa {mdgsa} | R Documentation |
Performs a Uni-Variate Gene Set Analysis using a logistic regression model.
uvGsa(index, annot, p.adjust.method = "BY", family = quasibinomial(), verbose = TRUE, verbosity = 100, fulltable = FALSE, ...)
index |
ranking index, generally a numerical named vector. |
annot |
an annotation list. |
p.adjust.method |
p-value adjustment method for multiple testing. |
family |
see |
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 |
'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".
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.
David Montaner dmontaner@cipf.es
mdGsa
, uvPat
,
glm.fit
, p.adjust
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