Comparison of Gene Set Analysis with Various Score Transformations to Test the Significance of Sets of Genes
| dc.contributor.author | Arreola, Ivan | |
| dc.contributor.author | Han, David | |
| dc.date.accessioned | 2020-06-08T22:29:41Z | |
| dc.date.available | 2020-06-08T22:29:41Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Microarray analysis can help identify changes in gene expression which are characteristic to human diseases. Although genomewide RNA expression analysis has become a common tool in biomedical research, it still remains a major challenge to gain biological insight from such information. Gene Set Analysis (GSA) is an analytical method to understand the gene expression data and extract biological insight by focusing on sets of genes that share biological function, chromosomal regulation or location. Thing systematic mining of different gene-set collections could be useful for discovering potential interesting gene-sets for further investigation. Here, we seek to improve previously proposed GSA methods for detecting statistically significant gene sets via various score transformations. | en_US |
| dc.description.department | Management Science and Statistics | |
| dc.identifier.issn | 2470-3958 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12588/61 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Office of the Vice President for Research | en_US |
| dc.relation.ispartofseries | The UTSA Journal of Undergraduate Research and Scholarly Work;Volume 4 | |
| dc.subject | Gene Expression | en_US |
| dc.subject | Gene Set Analysis | en_US |
| dc.subject | Gene Set Enrichment Analysis | en_US |
| dc.subject | Genomics | en_US |
| dc.subject | Micro-array Analysis | en_US |
| dc.title | Comparison of Gene Set Analysis with Various Score Transformations to Test the Significance of Sets of Genes | en_US |
| dc.type | Article | en_US |