'Multi-omic' data analysis using O-miner

Brief Bioinform. 2019 Jan 18;20(1):130-143. doi: 10.1093/bib/bbx080.

Abstract

Innovations in -omics technologies have driven advances in biomedical research. However, integrating and analysing the large volumes of data generated from different high-throughput -omics technologies remain a significant challenge to basic and clinical scientists without bioinformatics skills or access to bioinformatics support. To address this demand, we have significantly updated our previous O-miner analytical suite, to incorporate several new features and data types to provide an efficient and easy-to-use Web tool for the automated analysis of data from '-omics' technologies. Created from a biologist's perspective, this tool allows for the automated analysis of large and complex transcriptomic, genomic and methylomic data sets, together with biological/clinical information, to identify significantly altered pathways and prioritize novel biomarkers/targets for biological validation. Our resource can be used to analyse both in-house data and the huge amount of publicly available information from array and sequencing platforms. Multiple data sets can be easily combined, allowing for meta-analyses. Here, we describe the analytical pipelines currently available in O-miner and present examples of use to demonstrate its utility and relevance in maximizing research output. O-miner Web server is free to use and is available at http://www.o-miner.org.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computational Biology
  • DNA Methylation
  • Data Analysis*
  • Databases, Genetic / statistics & numerical data
  • Gene Dosage
  • Gene Expression Profiling / statistics & numerical data
  • Genomics / statistics & numerical data*
  • Humans
  • Internet
  • Neoplasms / genetics
  • Sequence Analysis, RNA / statistics & numerical data
  • Software Design
  • Software*
  • Whole Genome Sequencing / statistics & numerical data