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
fact:
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 fact.
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.
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
'factor1':this column has the name of the first category
'factor2':this column has the name of the second category
'factor3':this column has the name of the third category
n.'factor1':number of items in variable of first category
n.'factor2':number of items in variable of second category
n.'factor3':number of items in variable of third category
p.value:(probably adjusted) p-value
log2.odds.ratio:log2 of the sample odds ratio
n.tags:number of items at position x_{1,1,1} or x_{1,1}
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
showClass("concub")
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(geecc)
geecc 1.6.0 loaded
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/geecc/concub-class.Rd_%03d_medium.png", width=480, height=480)
> ### Name: concub-class
> ### Title: Class '"concub"'
> ### Aliases: concub-class getTable getTable,concub-method
> ### show,concub-method initialize,concub-method
> ### Keywords: classes
>
> ### ** Examples
>
> showClass("concub")
Class "concub" [package "geecc"]
Slots:
Name: fact population
Class: list character
Name: keep.empty.vars options
Class: list list
Name: approx null.model
Class: numeric formula
Name: test.result test.result.filter
Class: list list
Name: test.result.filter.heatmap
Class: list
>
>
>
>
>
> dev.off()
null device
1
>
providing 
.