Omics community detection using multi-resolution clustering
| Autor: | Himel Mallick, Suvo Chatterjee, Keith A. Crandall, Ali Rahnavard, Bahar Sayoldin, Fasil Tekola-Ayele |
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| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Supplementary data 0303 health sciences AcademicSubjects/SCI01060 Computer science business.industry Community structure Computational biology Omics Original Papers Biochemistry Computer Science Applications Omics data 03 medical and health sciences Computational Mathematics 0302 clinical medicine Software Computational Theory and Mathematics Multi resolution Data and Text Mining Cluster analysis business Molecular Biology 030217 neurology & neurosurgery 030304 developmental biology |
| Zdroj: | Bioinformatics |
| ISSN: | 1367-4811 1367-4803 |
| Popis: | Motivation The discovery of biologically interpretable and clinically actionable communities in heterogeneous omics data is a necessary first step toward deriving mechanistic insights into complex biological phenomena. Here, we present a novel clustering approach, omeClust, for community detection in omics profiles by simultaneously incorporating similarities among measurements and the overall complex structure of the data. Results We show that omeClust outperforms published methods in inferring the true community structure as measured by both sensitivity and misclassification rate on simulated datasets. We further validated omeClust in diverse, multiple omics datasets, revealing new communities and functionally related groups in microbial strains, cell line gene expression patterns and fetal genomic variation. We also derived enrichment scores attributable to putatively meaningful biological factors in these datasets that can serve as hypothesis generators facilitating new sets of testable hypotheses. Availability and implementation omeClust is open-source software, and the implementation is available online at http://github.com/omicsEye/omeClust. Supplementary information Supplementary data are available at Bioinformatics online. |
| Databáze: | OpenAIRE |
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