GREIN: An Interactive Web Platform for Re-analyzing GEO RNA-seq Data

The vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Inte...

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Bibliographic Details
Published in:Scientific reports 2019-05, Vol.9 (1), p.7580, Article 7580
Main Authors: Mahi, Naim Al, Najafabadi, Mehdi Fazel, Pilarczyk, Marcin, Kouril, Michal, Medvedovic, Mario
Format: Article
Language:English
Subjects:
38/39
38/91
631/114/794
631/337/2019
631/61/191/2018
Cell Hypoxia
Cell Line
Cell Line, Tumor
Computer applications
Female
Gene expression
Genomics - methods
Humanities and Social Sciences
Humans
Interfaces
Internet
multidisciplinary
Nucleotide sequence
Protein Biosynthesis
Ribonucleic acid
RNA
RNA processing
RNA-Seq - methods
Science
Science (multidisciplinary)
Software
Transcriptome
Triple Negative Breast Neoplasms - genetics
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Summary:The vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein , the source code at: https://github.com/uc-bd2k/grein , and the Docker container at: https://hub.docker.com/r/ucbd2k/grein .
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-019-43935-8