This article is part of the supplement: Eleventh International Conference on Bioinformatics (InCoB2012): Computational Biology
MicroRNA-centric measurement improves functional enrichment analysis of co-expressed and differentially expressed microRNA clusters
1 Seoul National University Biomedical Informatics (SNUBI) and Systems Biomedical Informatics Research Center, Div. of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, Korea
2 Institute of Endemic Diseases, Medical Research Center, Seoul National University, Seoul 110799, Korea
Citation and License
BMC Genomics 2012, 13(Suppl 7):S17 doi:10.1186/1471-2164-13-S7-S17Published: 13 December 2012
Functional annotations are available only for a very small fraction of microRNAs (miRNAs) and very few miRNA target genes are experimentally validated. Therefore, functional analysis of miRNA clusters has typically relied on computational target gene prediction followed by Gene Ontology and/or pathway analysis. These previous methods share the limitation that they do not consider the many-to-many-to-many tri-partite network topology between miRNAs, target genes, and functional annotations. Moreover, the highly false-positive nature of sequence-based target prediction algorithms causes propagation of annotation errors throughout the tri-partite network.
A new conceptual framework is proposed for functional analysis of miRNA clusters, which extends the conventional target gene-centric approaches to a more generalized tri-partite space. Under this framework, we construct miRNA-, target link-, and target gene-centric computational measures incorporating the whole tri-partite network topology. Each of these methods and all their possible combinations are evaluated on publicly available miRNA clusters and with a wide range of variations for miRNA-target gene relations. We find that the miRNA-centric measures outperform others in terms of the average specificity and functional homogeneity of the GO terms significantly enriched for each miRNA cluster.
We propose novel miRNA-centric functional enrichment measures in a conceptual framework that connects the spaces of miRNAs, genes, and GO terms in a unified way. Our comprehensive evaluation result demonstrates that functional enrichment analysis of co-expressed and differentially expressed miRNA clusters can substantially benefit from the proposed miRNA-centric approaches.