concub-class: Class '"concub"'

Description Details Objects from the Class Slots Methods See Also Examples

Description

An object of type concub

Details

Specifying the background population is crucial for the tests for association between factors. Usually the population is the set of all probe sets represented on a micro-array or the set of all genes in a genome. If an expression set is passed with the population-parameter, all probe sets beginning with the pattern “AFFX” (Affymetrix quality control) are removed.

Objects from the Class

Objects can be created by calls of the form new("concub", ...).

Slots

categories:

A named list of named lists. Each item of the outer list represents the two or three categories. Each item of the inner lists represents a variable of the category.

population:

A character vector containig the background population. As an alternative, an object with class ‘eSet’, ‘ExpressionSet’, or ‘DGEList’; background population is then set to the outcome of rownames(population).

keep.empty.vars:

A boolean list with names being names of categories.

options:

Additional options for individual categories. See Details.

approx:

specifies the minimum expected value when an exact hypergeometric test (below) or the chi-squared approximation should be used. Defaults to 0.

null.model:

A formula specifying the null-model of the test.

test.result:

A list to store test results. Filled up after runConCub.

test.result.filter:

A list to store filtered test results. Filled up after filterConCub.

test.result.filter.heatmap:

A list to store heatmaps for further manipulation. Filled up after plotConCub.

The last three slots are not set by the user.

Methods

getTable

signature(object = "concub"): creates a table containing the results of the tests.

Usage: getTable(object, na.rm=TRUE, dontshow=list())

Arguments:

object

an object of type concub

na.rm

logical. If TRUE (the default), rows with NA P-values (or odds ratios) are removed

The resulting table is a data frame with 8 or 10 columns, depending on if a two- or three-way test was applied

  1. 'factor1':this column has the name of the first category

  2. 'factor2':this column has the name of the second category

  3. 'factor3':this column has the name of the third category

  4. n.'factor1':number of items in variable of first category

  5. n.'factor2':number of items in variable of second category

  6. n.'factor3':number of items in variable of third category

  7. p.value:(probably adjusted) p-value

  8. log2.odds.ratio:log2 of the sample odds ratio

  9. n.tags:number of items at position x_{1,1,1} or x_{1,1}

  10. tags:items at position x_{1,1,1} or x_{1,1} (e.g. gene identifiers)

You have to run filterConCub() before you can get the table. If filterConCub() was not run, a warning is shown and getTable returns NULL.

show

signature(object = "concub")

See Also

GOStats to perform a simple two-way enrichment analysis

Examples

1
showClass("concub")

geecc documentation built on May 2, 2018, 3:07 a.m.