The Data Management, Analysis and Resources Dissemination Core will support the goals of the Broad Genomic Center for Infectious Diseases (GCID) by providing the software infrastructure and tools required for resource and data management, tracking, analysis and dissemination. The Data Core will leverage existing systems and the significant expertise of its personnel to establish and maintain an efficient resource and sample management process, develop a central data management and analysis infrastructure to support the scientific goals of the center, and ensure that high quality data are released rapidly to the scientific community in accordance with NIAID guidelines and instructions. The software infrastructure will flexibly and scalably support large-scale genome assembly, annotation, variant identification, transcriptome reconstruction, phylogenetic and functional comparisons and metagenomic data processing and analysis

Public Health Relevance

The Data Core will be an essential component of the GCID providing the component projects with a set of common production processes supported by a robust compute infrastructure that enables high-throughput sample tracking, metadata and data management, large scale analysis and the rapid release of high quality data and associated resources.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
1U19AI110818-01
Application #
8710836
Study Section
Special Emphasis Panel ()
Project Start
2014-04-10
Project End
2019-03-31
Budget Start
2014-04-10
Budget End
2015-03-31
Support Year
1
Fiscal Year
2014
Total Cost
$895,799
Indirect Cost
$326,035
Name
Broad Institute, Inc.
Department
Type
DUNS #
623544785
City
Cambridge
State
MA
Country
United States
Zip Code
02142
Diehl, William E; Lin, Aaron E; Grubaugh, Nathan D et al. (2016) Ebola Virus Glycoprotein with Increased Infectivity Dominated the 2013-2016 Epidemic. Cell 167:1088-1098.e6
Colubri, Andres; Silver, Tom; Fradet, Terrence et al. (2016) Transforming Clinical Data into Actionable Prognosis Models: Machine-Learning Framework and Field-Deployable App to Predict Outcome of Ebola Patients. PLoS Negl Trop Dis 10:e0004549
Malinga, Lesibana A; Abeel, Thomas; Desjardins, Christopher A et al. (2016) Draft Genome Sequences of Two Extensively Drug-Resistant Strains of Mycobacterium tuberculosis Belonging to the Euro-American S Lineage. Genome Announc 4:
Issi, Luca; Farrer, Rhys A; Pastor, Kelly et al. (2016) Members of the Zinc Cluster Factor Family Alters Virulence in Candida albicans. Genetics :
Anderson, Matthew Z; Porman, Allison M; Wang, Na et al. (2016) A Multistate Toggle Switch Defines Fungal Cell Fates and Is Regulated by Synergistic Genetic Cues. PLoS Genet 12:e1006353
Colgrove, Robert C; Liu, Xueqiao; Griffiths, Anthony et al. (2016) History and genomic sequence analysis of the herpes simplex virus 1 KOS and KOS1.1 sub-strains. Virology 487:215-21
Grant, Sarah Schmidt; Wellington, Samantha; Kawate, Tomohiko et al. (2016) Baeyer-Villiger Monooxygenases EthA and MymA Are Required for Activation of Replicating and Non-replicating Mycobacterium tuberculosis Inhibitors. Cell Chem Biol 23:666-77
Tewhey, Ryan; Kotliar, Dylan; Park, Daniel S et al. (2016) Direct Identification of Hundreds of Expression-Modulating Variants using a Multiplexed Reporter Assay. Cell 165:1519-29
Zhang, Danfeng; Gomez, James E; Chien, Jung-Yien et al. (2016) Genomic analysis of the evolution of fluoroquinolone resistance in Mycobacterium tuberculosis prior to tuberculosis diagnosis. Antimicrob Agents Chemother :
Caballero, Ignacio S; Honko, Anna N; Gire, Stephen K et al. (2016) In vivo Ebola virus infection leads to a strong innate response in circulating immune cells. BMC Genomics 17:707

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