Academic Journal
Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach
| Title: | Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach |
|---|---|
| Authors: | Mike Fang, Brian Richardson, Cheryl M. Cameron, Jean-Eudes Dazard, Mark J. Cameron |
| Source: | BMC Bioinformatics, Vol 22, Iss 1, Pp 1-14 (2021) |
| Publisher Information: | BMC, 2021. |
| Publication Year: | 2021 |
| Collection: | LCC:Computer applications to medicine. Medical informatics LCC:Biology (General) |
| Subject Terms: | Transcriptomics, Gene set enrichment analysis, Drug discovery, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5 |
| More Details: | Abstract Background In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Results We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting . Conclusions dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 1471-2105 |
| Relation: | https://doaj.org/toc/1471-2105 |
| DOI: | 10.1186/s12859-020-03929-0 |
| Access URL: | https://doaj.org/article/42800fa051264c41a3470bdcf2477a85 |
| Accession Number: | edsdoj.42800fa051264c41a3470bdcf2477a85 |
| Database: | Directory of Open Access Journals |
| Full text is not displayed to guests. | Login for full access. |
| ISSN: | 14712105 |
|---|---|
| DOI: | 10.1186/s12859-020-03929-0 |
| Published in: | BMC Bioinformatics |
| Language: | English |