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BD2K-LINCS-Perturbation Data Coordination & Integration Center

BD2K-LINCS-Perturbation Data Coordination & Integration Center. Applicant Information Webinar for RFA-HG-14-001 Ajay Pillai and Jennie Larkin January 13, 2013 1:00 - 2:30 PM EDT. RFA-HG-14- 001 Applicant Information Webinar

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BD2K-LINCS-Perturbation Data Coordination & Integration Center

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  1. BD2K-LINCS-Perturbation Data Coordination & Integration Center Applicant Information Webinar for RFA-HG-14-001 Ajay Pillai and Jennie Larkin January 13, 2013 1:00 - 2:30 PM EDT

  2. RFA-HG-14-001 Applicant Information Webinar • BD2K-LINCS-Perturbation Data Coordination and Integration Center (DCIC) (U54) • Today’s Webinar: • BD2K and LINCS program introduction • Overview of new FOA • Questions

  3. A trans-NIH initiative BD2K Mission enable biomedical scientists to capitalize more fully the Big Data being generated by the research community http://bd2k.nih.gov/ Big Data To Knowledge (BD2K): Overview

  4. BD2K: Background • Major challenges in using biomedical Big Data include: • Locating data and software tools. • Getting access to the data and software tools. • Standardizing data and metadata. • Extending policies and practices for data and software sharing. • Organizing, managing, and processing biomedical Big Data. • Developing new methods for analyzing & integrating biomedical data. • Training researchers who can use biomedical Big Data effectively.

  5. BD2K Centers • There was a separate call for Investigator-initiated Centers (RFA-HG-13-009) • This will be the first NIH-specified BD2K center. • This center will focus on perturbation – response data, including that generated by the LINCS consortium. • This Center will include the BD2K focus areas: • Collaborative environments and technologies • Data Integration

  6. LINCS: Library of Integrated Network-based Cellular Signatures Human cell types Phenotypicassays Perturbations • LINCS aims to inform a network-based understanding of biological systems in health and disease that can facilitate drug and biomarker development. • LINCS is: • Developing a library of molecular and cellular signatures that describe how different cell types respond to a variety of perturbations. • Addressing challenges in high-throughput data generation, data integration, annotation, and analysis. • Actively exploring collaborations with new biomedical research communities. • RNAi • small molecules • gene expression • protein level • metabolites http://lincsproject.org

  7. LINCS Program (2014 – 2020) • LINCS goals • inform a network-based understanding of cellular functions and response • expand the scope and richness of cellular responses to be measured. • support the addition of a broader and more informative range of human cell types, perturbations, and measurements. • LINCS Program Structure • 3-5 Data and Signature Generating Centers (RFA-RM13-013) to be funded in FY14 • One BD2K-LINCS Perturbagen Data Coordination and Integration Center (RFA-HG14-001) to be funded in FY15 • 6 year program with Mid-Course Review (~July 2017)

  8. Background:LINCS Data and Signature Generating Centers • Data and Signature production at scale, within first year of award (tens of thousands of data points per year) • Cell Types: human cells (cell lines, primary tissue, iPS cells and their differentiated derivatives) • Perturbagens: • Pilot: small molecules, growth factors, and genetic (knockdown or up-regulation by gene overexpression) • These will continue but applicants may propose other perturbations • Assays: • Should be medium to high throughput • Provide measures of wide interest to biomedical researchers • Should be flexible and amenable to multiple cell types • Should be replicable with high level of QC/QA under SOPs

  9. BD2K-LINCS PerturbagenDCICHG-14-001 • Aims in both section I and IV of RFA: read both carefully • 1 award, $5M in 2015. Future year amounts will depend on annual appropriations. • Application budget may be up to $3 million direct costs per year, not including the F&A costs of subcontracts. • 5-yr duration, it is a cooperative agreement • Familiarize yourself well with RFA-RM-13-013 • Data science is described in RFA-HG-13-009.

  10. BD2K-LINCS PerturbagenDCICGoals • address significant data science challenges associated with perturbagen-response datasets • establish a community resource for perturbagen-response data • coordinate LINCS consortium activities • Goal: enable advances in understanding of cellular function and its relationship with disease and normal biology

  11. BD2K-LINCS Perturbagen DCIC • Integrated Knowledge Environment • Data Integration: • integrating LINCS data with other perturbation data and other non-perturbation datasets • Collaborative Environments and Technologies: • utilize novel methods to provide access while supporting data attribution and provenance • Support Unified Access to LINCS DSGC Resources: • Support single-point of access for community to DSGC and DCIC tools & data • For bench & computational scientists

  12. LINCS Data/Signature Access • Each DSGC will build an appropriate database and an underlying infrastructure to support queries and other analytical requirements on their datasets • Metadata annotation by DSGCs for both data and software resources is crucial. • LINCS will have a distributed data resource and infrastructure to support queries • LINCS aims to create a single user interface via the separate DCIC for all of the LINCS resources for all biomedical researchers, including computational biologists

  13. BD2K-LINCS Perturbagen DCIC • Data Science Research Collaborations • Internal innovative DSR projects related to perturbation data; short-term; adaptable/flexible; • External Data Science Collaborations: • bring in novel expertise and analytical capabilities, to engage in high-risk high-reward approaches • set aside $700,000 in direct costs each year • identify 3collaborative projects (lasting 12 months) with groups that are not part of the application • Propose a plan to identify three such innovative projects each year of the funded grant

  14. BD2K-LINCS Perturbagen DCIC • Consortium Coordination and Administration • May request up to $100,000/yrfor BD2K coordination efforts • Support Incorporation of LINCS-related Data Types from External Resources • You do not expected to replicate other databases, but can retain relevant indexes/summaries for efficiency in retrieval • Coordinate Annotation of Data, Tools, and Resources • Enable coordination activities for the LINCS consortium (DSGCs and the DCIC)

  15. BD2K-LINCS Perturbagen DCIC • Community Training and Outreach • Data science • address questions of access and use of perturbation-type by community • Access to LINCS Resources • Work with LINCS DSGC to establishing the LINCS resource & approach within multiple biomedical communities. • Propose how your training/outreach will enable subsets of the biomedical community to leverage the whole LINCS resource.

  16. DCIC: program administration • Cooperative agreement, with substantial collaboration between LINCS grantees and involvement of program staff. • Integral part of LINCS Steering Committee with relevant and appropriate leadership role to enable overall LINCS goals. • Participate in BD2K Working Groups and other suitable activities including annual BD2K meetings. • Questions: lincsproject@mail.nih.gov

  17. DCIC: Review • Reviewers will provide an impact score for each component of the Center; Impact score of the Overall Component is the impact score of the entire application. • Some significant questions: • data integration challenges within and across LINCS & other existing public resources • single user-interface for all LINCS data & signature • community access & scalability • coordination & metadata for LINCS • integration of components of the center

  18. Appendix

  19. NIH Common Fund • Supports cross-cutting programs that are expected to have exceptionally high impact. • Develops bold, innovative, and often risky approaches to address problems that may seem intractable or to seize new opportunities that offer the potential for rapid progress. • NIH LINCS Program Co-Chairs: • Alan Michelson, PhD (NHLBI) • Mark Guyer, PhD (NHGRI) • NIH LINCS Coordinators • Ajay Pillai, PhD (NHGRI) • Jennie Larkin, PhD (NHLBI)

  20. LINCS Pilot Phase (2010 – 2013) • Pilot goals: • Develop a limited yet coherent data, and signature resource that could be used by the general research community. • Identify key issues in data annotation, integration, and analysis. • Pilot activities: • Two data and signature generating U54 awards • Development of new high-throughput assays to detect perturbation-induced cellular responses • Novel computational methods for integrative data analysis • Active collaborations and working groups http://lincsproject.org

  21. Background:LINCS Data and Signature Generating Centers • RFA-RM13-013 (going to May 2014 Council) • Will fund 3-5 DSGC awards • Part of a collaborative LINCS program • DSGC structure: • Data Generation (40% effort) • Data Analysis and Signature Identification (40% effort) • Community Interactions Outreach • Administrative • (20% effort)

  22. BD2K Centers • A combination of Investigator-Initiated and NIH-specifiedCenters • Centers to conduct research & provide resources • Centers will form an interactive consortium • Investigator Initiated Centers FOA : Centers of Excellence for Big Data Computing in the Biomedical Sciences (U54) RFA-HG-13-009 • 6-8 will be funded Summer 2014. • Potential Centers focus areas: • Collaborative environments and technologies • Data Integration • Analysis and modeling methods • Computer science and statistical approaches

  23. NIH Big Data to Knowledge (BD2K)Programmatic Areas • Facilitating Broad Use of Biomedical Big Data: Mike Huerta NLM & Jennie Larkin NHLBI II. Developing and Disseminating Analysis Methods and Software for Biomedical Big Data: Vivien Bonazzi NHGRI & Jennifer Couch NCI III. Enhancing Training for Biomedical Big Data: Michelle Dunn NCI IV. Establishing Centers of Excellence for Biomedical Big Data: Lisa Brooks NHGRI, Mike Huerta NLM, Peter Lyster NIGMS & Belinda Seto NIBIB)

  24. Perturbation DCIC: linking two programs (BD2K and LINCS) • BD2K: supports necessary advances in data science, other quantitative sciences, policy, and training to support the effective use of Big Data in biomedical research. • LINCS: promote a new understanding of health and disease through an integrative approach that identifies common patterns (signatures) in molecular and cellular responses to a wide range of perturbations, including small molecules, other environmental stimuli, genetic variation, and disease

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