4.7 Article

Multiomix: a cloud-based platform to infer cancer genomic and epigenomic events associated with gene expression modulation

期刊

BIOINFORMATICS
卷 38, 期 3, 页码 866-868

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btab678

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资金

  1. National Agency of Scientific and Technological Promotion [PICT-2018-01403]
  2. Universidad Abierta Interamericana (UAI)
  3. Universidad Nacional de La Plata (UNLP)

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Multiomix is an interactive cloud-based platform that helps biologists identify genetic and epigenetic events associated with the transcriptional modulation of cancer-related genes. Users can analyze data from public functional genomic databases or upload their own datasets. Multiomix provides a range of functions, pipelines, and a graphical user interface for retrieving, aggregating, analyzing, and visualizing different omics data sources.
Motivation: Large-scale cancer genome projects have generated genomic, transcriptomic, epigenomic and clinicopathological data from thousands of samples in almost every human tumor site. Although most omics data and their associated resources are publicly available, its full integration and interpretation to dissect the sources of gene expression modulation require specialized knowledge and software. Results: We present Multiomix, an interactive cloud-based platform that allows biologists to identify genetic and epigenetic events associated with the transcriptional modulation of cancer-related genes through the analysis of multiomics data available on public functional genomic databases or user-uploaded datasets. Multiomix consists of an integrated set of functions, pipelines and a graphical user interface that allows retrieval, aggregation, analysis and visualization of different omics data sources. After the user provides the data to be analyzed, Multiomix identifies all significant correlations between mRNAs and non-mRNA genomics features (e.g. miRNA, DNA methylation and CNV) across the genome, the predicted sequence-based interactions (e.g. miRNA-mRNA) and their associated prognostic values.

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