dsea_GSEA {signatureSearch} | R Documentation

## Drug Set Enrichment Analysis (DSEA) with GSEA Algorithm

### Description

The `dsea_GSEA` function performs Drug Set Enrichment Analysis (DSEA) with the GSEA algorithm from Subramanian et al. (2005). In case of DSEA, drug identifiers combined with their ranking scores of an upstream GESS method are used, such as the NCS values from the LINCS method. To use drug instead of gene labels for GSEA, the former are mapped to functional categories, including GO or KEGG, based on drug-target interaction annotations provided by databases such as DrugBank, ChEMBL, CLUE or STITCH.

### Usage

    dsea_GSEA(
      drugList,
      type = "GO",
      ont = "BP",
      exponent = 1,
      nPerm = 1000,
      minGSSize = 10,
      maxGSSize = 500,
      pvalueCutoff = 0.05,
      pAdjustMethod = "BH"
    )

### Arguments

`drugList` | named numeric vector, where the names represent drug labels and the numeric component scores. This can be all drugs of a GESS result that are ranked by GESS scores, such as NCSs of the LINCS method. Note, drugs with scores of zero are ignored by this method.
`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.
`exponent` | integer value used as exponent in GSEA algorithm. It defines the weight of the items in the item set S. Note, in DSEA the items are drug labels, while it is gene labels in the original GSEA.
`nPerm` | integer defining the number of permutation iterations for calculating p-values
`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.
`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'

### Details

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_mGSEA` function.

### Value

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

### References

GSEA algorithm: Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Mesirov, J. P. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America, 102(43), 15545-15550. URL: https://doi.org/10.1073/pnas.0506580102

### See Also

`feaResult`, `fea`, `GO_DATA_drug`

### Examples

    data(drugs10)
    dl <- c(rev(seq(0.1, 0.5, by=0.05)), 0)
    names(dl)=drugs10
    ## KEGG annotation system
    #gsea_k_res <- dsea_GSEA(drugList=dl, type="KEGG", exponent=1, nPerm=100,
    #                        pvalueCutoff=0.5, minGSSize=2)
    #result(gsea_k_res)

[Package signatureSearch version 1.1.5 Index]