uvGsa {mdgsa} | R Documentation

## 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'.

### 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 dmontaner@cipf.es

### 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

[Package mdgsa version 1.16.0 Index]