1. ‘Multi-omic’ data analysis using O-miner
- Author
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Sangaralingam, Ajanthah, Dayem Ullah, Abu Z, Marzec, Jacek, Gadaleta, Emanuela, Nagano, Ai, Ross-Adams, Helen, Wang, Jun, Lemoine, Nicholas R, and Chelala, Claude
- Subjects
Paper ,Data Analysis ,O-miner ,Internet ,Whole Genome Sequencing ,Sequence Analysis, RNA ,Gene Expression Profiling ,Gene Dosage ,Computational Biology ,sequencing ,Genomics ,multi-omics ,DNA Methylation ,Software Design ,Neoplasms ,Databases, Genetic ,Humans ,data integration ,Software - 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.
- Published
- 2017