Djordjevic, Djordje and Tang, Joshua Y.S. and Chen, Yun Xin and Kwan, Shu Lun Shannon and Ling, Raymond W.K. and Qian, Gordon and Woo, Chelsea Y.Y. and Ellis, Samuel J. and Ho, Joshua W.K. (2019) Discovery of perturbation gene targets via free text metadata mining in Gene Expression Omnibus. Computational Biology and Chemistry, 80. pp.152-158. ISSN 14769271
Full text not available from this repository.Abstract
There exists over 2.5 million publicly available gene expression samples across 101,000 data series in NCBI's Gene Expression Omnibus (GEO) database. Due to the lack of the use of standardised ontology terms in GEO's free text metadata to annotate the experimental type and sample type, this database remains difficult to harness computationally without significant manual intervention. In this work, we present an interactive R/Shiny tool called GEOracle that utilises text mining and machine learning techniques to automatically identify perturbation experiments, group treatment and control samples and perform differential expression. We present applications of GEOracle to discover conserved signalling pathway target genes and identify an organ specific gene regulatory network. GEOracle is effective in discovering perturbation gene targets in GEO by harnessing its free text metadata. Its effectiveness and applicability has been demonstrated by cross validation and two real-life case studies. It opens up new avenues to unlock the gene regulatory information embedded inside large biological databases such as GEO. GEOracle is available at https://github.com/VCCRI/GEOracle.
| Item Type: | Article |
|---|---|
| Subjects: | R Medicine > R Medicine (General) |
| Depositing User: | Repository Administrator |
| Date Deposited: | 27 May 2019 22:36 |
| Last Modified: | 27 May 2019 22:36 |
| URI: | https://eprints.victorchang.edu.au/id/eprint/836 |
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