NHGRI/DIR Scientific Computing

National Human Genome Research Institute

Investigators

Abstract

The NHGRI Division of Intramural Research maintains a robust computational infrastructure for specialized research computing. These resources are provided to support the Division's broad program of genomic, bioinformatic, clinical, and behavioral research aimed at translating genomic and genetic research into a greater understanding of human genetic disease, as well as towards developing better methods for the detection, prevention, and treatment of heritable and genetic disorders. NHGRI/DIR provides significant computational support for its high-throughput research efforts in whole-genome sequencing, whole-genome association studies, clinical variant discovery, and similar types of genome-wide analyses. These approaches generate enormous amounts of data (on the order of terabytes) in a single run, thereby requiring strong database solutions, innovative storage and archiving strategies, and a reliable high-performance computing environment, one that can keep pace with the ever-increasing rate at which large-scale biological and biomedical data are being generated. NHGRI/DIR maintains a suite of commercial and public domain software for handling the wide range of needs of NHGRI investigators. The list includes software for DNA and protein sequence analysis, molecular modeling, expression analysis (including single-cell analysis), pathway analysis, biostatistics, and the analysis of data being generated by whole-genome association studies. In addition, realizing the importance of providing NHGRI scientists with a robust database in support of their clinical research efforts, a Web-based and HIPAA-compliant database with an integrated pedigree viewer and SQL querying tool has been available to all NHGRI investigators conducting clinical protocols aimed at understanding the underlying mechanisms of a wide variety of human genetic disorders. This clinical database's functionality allows for the automated import of clinical laboratory data from the NIH Clinical Center's Clinical Research Information System (CRIS) data warehouse and from NIH's Biomedical Translation Research Information System (BTRIS). Future efforts in the clinical informatics arena will focus on migration to REDCap, a browser-based, metadata-driven electronic data capture software and workflow methodology that has been widely adopted within the NIH and by our peer institutions in support of clinical and translational research efforts.