‘Multi-omic’ data analysis using O-miner

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.

Multi-omics Data Integration, Interpretation, and Its Application

“…The approach must perform an integrative step wherein multiple data sets are analyzed in a simultaneous manner (parallel integration of data sets and not sequential). Platforms such as Galaxy 11 and O-Miner 12 that help in analyzing multi-omics data, albeit individually, are not part of this review. 2.…”

Wheat Omics: Advancements and Opportunities

“…Various web-based tools and visualization portals are available to analyze the multi-omics datasets, such as PAINTOMICS, KaPPA-view, COVAIN, and O-miner [ 174 , 175 , 176 , 177 , 178 ]. In PAINTOMICS, the integrated visualization of transcriptomics and metabolomics datasets is possible and displays the data on KEGG pathway maps.…”

OpenOmics: A bioinformatics API to integrate multi-omics datasets and interface with public databases.

“…Second, MixOmics is an R library dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. Third, O-Miner (Sangaralingam et al, 2019) is web tool that provides a pipeline for analysis of both transcriptomic and genomic data starting from raw image files through in-depth bioinformatics analysis. However, as large-scale multi-omic data analysis demands continue to grow, the technologies and data analysis needs continually change to adapt with big data.…”