Gene set analysis methods for the functional interpretation of non-mRNA data-Genomic range and ncRNA data.
review · Level V
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- Record sourced from PubMed, PMID 31612220.
- Also identified by DOI 10.1093/bib/bbz090.
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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.
Medical subject headings
- Gene Regulatory Networks
- Genomics
- Machine Learning
- RNA, Long Noncoding
- RNA, Messenger