extractGOseq {SMITE} | R Documentation

## View the GOseq pathway analysis after having run Goseq, or search for a term.

### Description

Having defined at least one genomic module using runSpinglass or runBioNet, this function allows you to interrogate the enriched terms for a specific module or combination of modules.

### Usage

    extractGOseq(pvalue_annotation, which_network = NULL)
    searchGOseq(pvalue_annotation, search_string, wholeword = FALSE)

### Arguments

`pvalue_annotation` | An S4 object of class PvalueAnnotation, for which module-finding and GOseq analysis have already been performed
`which_network` | A numeric vector of a length of at least one, corresponding to a particular functional module specifically for the extract function.
`search_string` | A character specfying a search string specifically for the search function.
`wholeword` | A logical (TRUE/FALSE) detemring whether the search string must be matched for whole word specifically for the search function.

### Details

Goseq analysis is useful since it allows you to assess term/pathway enrichment in a collection of genes, while adjusting for bias data. Potential bias can be from aspects like gene length or probe density that influence the likelihood of finding a particular gene. For more information please see the goseq reference.

### Value

##Extract## A list with eahc element matching the specified module. Has columns identfying the term id, the over represented p-value, underrepresented p-value the total number in the category found in the module, the total number in the category and a more descirptive pathway name.

##Search## A matrix with columns identfying the module name, module position/significance , the specific enriched term, the rank of that term within all enriched terms and the total number of enriched terms.

### Author(s)

N. Ari Wijetunga

### References

Young MD, Wakefield MJ, Smyth GK and Oshlack A (2010). Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biology, 11, pp. R14.

### See Also

runGOseq runSpinglass runBioNet extractModules plotModule

### Examples

    ## Commented out below.  See vignette for more details ##

    ##load sample data with only PvalueObject filled in##
    data(test_annotation_score_data)

    ## show goseq analysis for module 1 ##
    extractGOseq(test_annotation, 1)

    ## show goseq analysis for module 1 and 2 ##
    #extractGOseq(test_annotation, 1:2)

    ## search for term ##

    #searchGOseq(test_annotation, "Cell cycle")

[Package SMITE version 1.8.0 Index]