Unknown

Dataset Information

0

'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.

SUBMITTER: Sangaralingam A 

PROVIDER: S-EPMC6357557 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

altmetric image

Publications


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  ...[more]

Similar Datasets

| S-EPMC5937130 | biostudies-literature
| S-EPMC5994057 | biostudies-literature
| PRJNA790956 | ENA
| S-EPMC6781126 | biostudies-literature
| S-EPMC6457037 | biostudies-literature
| S-EPMC3397418 | biostudies-literature
| S-EPMC8128416 | biostudies-literature
2022-04-01 | GSE191312 | GEO
| S-EPMC4324155 | biostudies-literature
| S-EPMC9913631 | biostudies-literature