View source: R/gcn_inference.R
module_enrichment | R Documentation |
Perform enrichment analysis for coexpression network modules
module_enrichment(
net = NULL,
background_genes,
annotation,
column = NULL,
correction = "BH",
p = 0.05,
min_setsize = 10,
max_setsize = 500,
bp_param = BiocParallel::SerialParam()
)
net |
List object returned by |
background_genes |
Character vector of genes to be used as background for the Fisher's Exact Test. |
annotation |
Annotation data frame with genes in the first column and functional annotation in the other columns. This data frame can be exported from Biomart or similar databases. |
column |
Column or columns of |
correction |
Multiple testing correction method. One of "holm", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr" or "none". Default is "BH". |
p |
P-value threshold. P-values below this threshold will be considered significant. Default is 0.05. |
min_setsize |
Numeric indicating the minimum gene set size to be considered. Gene sets correspond to levels of each variable in annotation). Default: 10. |
max_setsize |
Numeric indicating the maximum gene set size to be considered. Gene sets correspond to levels of each variable in annotation). Default: 500. |
bp_param |
BiocParallel back-end to be used. Default: BiocParallel::SerialParam() |
A data frame of overrepresentation results with the following variables:
character, functional term ID/name.
numeric, intersection length between input genes and genes in a particular functional term.
numeric, number of all genes in a particular functional term.
numeric, P-value for the hypergeometric test.
numeric, P-value adjusted for multiple comparisons using the method specified in parameter adj.
character, name of the grouping variable (i.e., column name of annotation).
character, module name.
Fabricio Almeida-Silva
data(filt.se)
data(zma.interpro)
background <- rownames(filt.se)
gcn <- exp2gcn(filt.se, SFTpower = 18, cor_method = "pearson")
mod_enrich <- module_enrichment(gcn, background, zma.interpro, p=1)
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