| Literature DB >> 31612220 |
Abstract
Gene set analysis (GSA) is one of the methods of choice for analyzing the results of current omics studies; however, it has been mainly developed to analyze mRNA (microarray, RNA-Seq) data. The following review includes an update regarding general methods and resources for GSA and then emphasizes GSA methods and tools for non-mRNA omics datasets, specifically genomic range data (ChIP-Seq, SNP and methylation) and ncRNA data (miRNAs, lncRNAs and others). In the end, the state of the GSA field for non-mRNA datasets is discussed, and some current challenges and trends are highlighted, especially the use of network approaches to face complexity issues.Entities:
Keywords: ChIP-Seq; SNP; gene set analysis; lncRNA; methylation; miRNA; pathway analysis
Year: 2019 PMID: 31612220 DOI: 10.1093/bib/bbz090
Source DB: PubMed Journal: Brief Bioinform ISSN: 1467-5463 Impact factor: 11.622