dsea_hyperG {signatureSearch} | R Documentation

## Drug Set Enrichment Analysis (DSEA) with Hypergeometric Test

### 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)

[Package signatureSearch version 1.0.4 Index]