RT Journal Article
SR Electronic
T1 GEOracle: Mining perturbation experiments using free text metadata in Gene Expression Omnibus
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 150896
DO 10.1101/150896
A1 Djordje Djordjevic
A1 Yun Xin Chen
A1 Shu Lun Shannon Kwan
A1 Raymond W. K. Ling
A1 Gordon Qian
A1 Chelsea Y. Y. Woo
A1 Samuel J. Ellis
A1 Joshua W. K. Ho
YR 2017
UL http://biorxiv.org/content/early/2017/06/16/150896.abstract
AB Summary There exists over 1.6 million publicly available gene expression samples across 79,000 data series in NCBI’s Gene Expression Omnibus database. Due to the lack of the use of standardised ontology terms 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.Availability GEOracle is available at http://georacle.victorchang.edu.au/Contact jho{at}victorchang.edu.auSupplementary information Supplementary data are available at BioRXiv