dsea_hyperG: Drug Set Enrichment Analysis (DSEA) with Hypergeometric Test

In signatureSearch: Environment for Gene Expression Searching Combined with Functional Enrichment Analysis

Description

The dsea_hyperG function performs Drug Set Enrichment Analysis (DSEA) based on the hypergeomtric distribution. In case of DSEA, the identifiers of the top ranking drugs from a GESS result table are used. To use drug instead of gene labels for this test, the former are mapped to functional categories, including GO, KEGG or Mode of Action (MOA) categories, based on drug-target interaction annotations provided by databases such as DrugBank, ChEMBL, CLUE or STITCH. Currently, the MOA annotation used by this function are from the CLUE website (https://clue.io).

Usage

dsea_hyperG(
  drugs,
  type = "GO",
  ont = "BP",
  pvalueCutoff = 0.05,
  pAdjustMethod = "BH",
  qvalueCutoff = 0.2,
  minGSSize = 10,
  maxGSSize = 500
)

Arguments

drugs	character vector, query drug identifier set used for functional enrichment testing. This can be the top ranking drugs from a GESS result.
type	one of 'GO', 'KEGG' or 'MOA'
ont	character(1). If type is 'GO', assign ont (ontology) one of ‘BP','MF', 'CC' or 'ALL'. If type is ’KEGG', ont is ignored.
pvalueCutoff	double, p-value cutoff to return only enrichment results for drugs meeting a user definable confidence threshold
pAdjustMethod	p-value adjustment method, one of 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr'
qvalueCutoff	double, qvalue cutoff, similar to pvalueCutoff
minGSSize	integer, annotation categories with less than minGSize drugs annotated will be ignored by enrichment test. If type is 'MOA', it may be beneficial to set 'minGSSize' to lower values (e.g. 2) than for other functional annotation systems. This is because certain MOA categories contain only 2 drugs.
maxGSSize	integer, annotation categories with more drugs annotated than maxGSize will be ignored by enrichment test.

Details

Compared to the related Target Set Enrichment Analysis (TSEA; see help tsea_dup_hyperG or tsea_mGSEA), the DSEA approach has the advantage that the drugs in the query test sets are usually unique allowing to use them without major modifications to the underlying statistical method(s).

The DSEA results stored in the feaResult object can be returned with the result method in tabular format, here tibble. The columns of this tibble are described in the help of the tsea_dup_hyperG function.

Value

feaResult object containing the enrichment results of functional categories (e.g. GO terms or KEGG pathways) ranked by the corresponding enrichment statistic.

See Also

feaResult, fea, GO_DATA_drug

Examples

data(drugs10)
## GO annotation system
# hyperG_res <- dsea_hyperG(drugs = drugs10, type = "GO", ont="MF")
# result(hyperG_res)
## KEGG annotation system
#hyperG_k_res <- dsea_hyperG(drugs = drugs10, type = "KEGG", 
#                            pvalueCutoff = 1, qvalueCutoff = 1, 
#                            minGSSize = 10, maxGSSize = 500)
#result(hyperG_k_res) 

signatureSearch documentation built on April 16, 2021, 6 p.m.