kobas.identify {KOBAS} R Documentation

Run the KOBAS style over-representation (enrichment) analysis

Description

<br /> Perform the over-representation analysis with the KOBAS statistical tests: the<br /> foreground gene list is mapped onto the given gene set collection, then the<br /> members of each term are compared with the background gene list by the<br /> hypergeometric test, the Fisher exact test, the binomial test or the chi-square<br /> test.

Usage

kobas.identify(foreground, background, gmt,
    method = "h",
    fdr = "BH",
    cutoff = 5,
    database = "K");

Arguments

foreground

the foreground gene list: a character vector of the gene ids, or the file path of a KOBAS annotate output file (the query column will be used).

background

the background gene list: a character vector of the gene ids, or the file path of a KOBAS annotate output file. It must be a superset of the foreground for the Fisher and the chi-square test.

gmt

the gene set collection: a Background model or a GMT file path.

method

the statistical test: h for the Fisher exact test (default, also the hypergeometric test), b for the binomial test, c for the chi-square test and x for the frequency list only. [as string]

fdr

the multiple testing correction: BH (default), BY, QVALUE or None. [as string]

cutoff

the minimum number of the background members of a term, terms with fewer background members are not used in the statistical test. Default 5. [as integer]

database

the database label that will be written into the database column, default K (KEGG PATHWAY). [as string]

env

the R# runtime environment. [as Environment]

Details

Authors

gseakit

Value

a dataframe with the term id as the row names and the columns: name, database, input_number, background_number, pvalue, p_adjust and input (the enriched gene ids joined by ;).

clr value class

Examples

[Package KOBAS version 1.0.0.0 Index]