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

Abstract

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 .

Keywords: Bioinformatics; Cloud computing; Genotype-phenotype integration; Next generation sequencing; Outcomes research; Precision medicine; Translational research; Variant analysis.

Fig. 1

Summary of G-DOC Plus data management and analysis features

Fig. 2

Summary of G-DOC Plus tools under each workflow

Fig. 3

a General system architecture of G-DOC Plus. b Summary of plugins in G-DOC Plus. The plugins marked in * indicate open source plugins that were customized for G-DOC Plus

Fig. 4

The workflow used to extract information for the 1000 genomes dataset in G-DOC Plus. The pre-processed data was about 132 GB in size and stored in Mongo DB on the Amazon cloud for quick and efficient data retrieval

Fig. 5

a and b Pathway enrichment and gene network in G-DOC Plus

Fig. 6

a Heat map comparing Astrocytoma and GBM patients. Over-expression of genes in the heat map is represented in red color, and under-expression is shown in green color. b Chromosome instability in chromosome 8. Here, black color indicates normal DNA copy number (i.e. no instability); and the red color indicates instability - higher the instability, the brighter the red color on the heatmap. c Kaplan Meier survival plot between Astrocytoma (red line) and Glioblastoma patients (blue line)

Fig. 7

a Selection of medical images based on clinical data of patient(s). b Screen shot of the medical MRI imaging module in G-DOC Plus