G-DOC Plus – an integrative bioinformatics platform for precision medicine

• Published in: BMC bioinformatics Vol. 17; no. 1; p. 193
• Main Authors: Bhuvaneshwar, Krithika, Belouali, Anas, Singh, Varun, Johnson, Robert M., Song, Lei, Alaoui, Adil, Harris, Michael A., Clarke, Robert, Weiner, Louis M., Gusev, Yuriy, Madhavan, Subha
• Format: Journal Article
• Language: English
• Published: London BioMed Central 30.04.2016
• Subjects: Algorithms; Bioinformatics; Biomedical and Life Sciences; Computational Biology - methods; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Databases, Factual; Humans; Life Sciences; Microarrays; Neoplasms - genetics; Oligonucleotide Array Sequence Analysis; Precision Medicine - methods; Results and data; Software; Transcriptome; Cloud computing; Translational research; Precision medicine; Variant analysis; Genotype-phenotype integration; Outcomes research; Bioinformatics; Next generation sequencing
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-016-1010-0

Background G-DOC Plus is a data integration and bioinformatics platform that uses cloud computing and other advanced computational tools to handle a variety of biomedical BIG DATA including gene expression arrays, NGS and medical images so that they can be analyzed in the full context of other omics and clinical information. Results G-DOC Plus currently holds data from over 10,000 patients selected from private and public resources including Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the recently added datasets from REpository for Molecular BRAin Neoplasia DaTa (REMBRANDT), caArray studies of lung and colon cancer, ImmPort and the 1000 genomes data sets. The system allows researchers to explore clinical-omic data one sample at a time, as a cohort of samples; or at the level of population, providing the user with a comprehensive view of the data. G-DOC Plus tools have been leveraged in cancer and non-cancer studies for hypothesis generation and validation; biomarker discovery and multi-omics analysis, to explore somatic mutations and cancer MRI images; as well as for training and graduate education in bioinformatics, data and computational sciences. Several of these use cases are described in this paper to demonstrate its multifaceted usability. Conclusion G-DOC Plus can be used to support a variety of user groups in multiple domains to enable hypothesis generation for precision medicine research. The long-term vision of G-DOC Plus is to extend this translational bioinformatics platform to stay current with emerging omics technologies and analysis methods to continue supporting novel hypothesis generation, analysis and validation for integrative biomedical research. By integrating several aspects of the disease and exposing various data elements, such as outpatient lab workup, pathology, radiology, current treatments, molecular signatures and expected outcomes over a web interface, G-DOC Plus will continue to strengthen precision medicine research. G-DOC Plus is available at: https://gdoc.georgetown.edu .