期刊
BRIEFINGS IN BIOINFORMATICS
卷 21, 期 5, 页码 1495-1508出版社
OXFORD UNIV PRESS
DOI: 10.1093/bib/bbz090
关键词
pathway analysis; gene set analysis; ChIP-Seq; SNP; methylation; miRNA; lncRNA
资金
- Joint School of Life Sciences, Guangzhou Medical University
- Guangzhou Institutes of Biomedicine and Health (Chinese Academy of Sciences)
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.
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