ARCHIVED: Project: Supporting the Michael Lynch Lab for NSF Grant: Methods for the Analysis of Population-Genomic Data

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Primary UITS contact: Robert Henschel

Last update: July 11, 2014

Description: The Michael Lynch Lab in the Indiana University Biology department has received a grant award from the NSF that is in effect from February 2013 through January 2016. The grant proposal is entitled "Methods for the Analysis of Population-Genomic Data". As part of the grant proposal, Dr. Lynch included funds to provide ongoing support to aid his team of biologists in leveraging cyberinfrastructure at the university and national levels. The SciAPT team from the Research Technologies division of UITS is taking on the role of supporting the Lynch Lab for their cyberinfrastructure needs.

The work supported by the grant award will develop a general statistical framework for the analysis of population-genomic data. The general strategy is to derive and computationally validate a set of efficient estimators for population-genetic parameters at three levels: individual genomes, multiple individuals within populations, and multiple populations. Specific subprojects include the measurement of patterns of variation and covariation among nucleotide sites, levels of population subdivision, and the development of novel methods to facilitate genome assembly and the refinement of genetic maps. Considerable emphasis will be focused on the development of efficient estimation algorithms for use by the genomics research community. SciAPT will focus on applying its expertise in scientific data analysis and algorithm optimization for Big Data and High Performance Computing challenges to the task of developing efficient, robust, and accurate estimator algorithms.

Outcomes: SciAPT will accelerate the development of a general statistical framework for the analysis of population-genomic data by the Lynch Lab. At the end of the grant award period, we expect to have a fully distributable set of tools that scientists can use to produce accurate population-genetic estimators using large scale data sets.

Milestones and status:

  • Select a data storage technology Completed
  • Optimization of allele frequency estimator for groups of individuals Completed
  • Complete testing and debugging of allele frequency estimator Completed
  • Development of a parallel allele frequency estimator for groups of individuals Completed
  • Development of software to ingest genome data into SQL database Completed
  • Optimization of allele frequency estimator for groups of individuals Completed
  • Complete testing and debugging of allele frequency estimator Completed
  • Create the SQL database, index it, and successfully run the frequency estimator program Completed
  • Add statistical discriminator to allele frequency estimator In progress
  • Develop and debug individual genotype estimator In progress
  • Plan and prepare for a workshop in summer of 2015 In progress

Comment process: Email comments to Robert Henschel.

Aids achievement of the following Empowering People actions:

  • Recommendation A1
    • Action 4: Cyberinfrastructure. IU should continue to advance its local cyberinfrastructure, participation in national cyberinfrastructure, and its efforts to win federal funding of cyberinfrastructure programs that enhance IU's research capabilities.
  • Recommendation A4
    • Action 16: External funding. OVPIT should continue to lead and expand its efforts to effectively partner with academic units, campuses, administrative units, or individual investigators for external funding opportunities.
  • Recommendation A7
    • Action 25: Research into IT. IU should support and pursue research into information technology itself. IT professionals and faculty should seek partnership opportunities for scholarly publication and invention disclosure that document meritorious research and discovery. (PTI leads; RT supporting)
  • Recommendation C15
    • Action 70: IT-enabled research. IU should purposefully select areas of great and timely promise for strategic development of IT-enabled research, scholarship, and/or creative activity. (PTI leads)
    • Action 71: IT-enabled research resources. IU should identify a base of resources to provide both initial and sustained investments in selected areas for IT-enabled research, scholarship, and/or creative activity. This may include reallocating current resources and developing new ones, including endowments, grants, and/or additional fees. (RT leads)
    • Action 72: IT research hiring. IU should carefully assess new skills that are necessary to advance promising opportunities as research becomes more IT-intensive. Campus, school, and departmental leaders should help to target some strategic hiring to supply or augment expertise for advanced, IT-enabled research and creative activity. (RT leads)

UITS project team:

  • Abhinav Thota
  • Robert Henschel

Governance:

  • UITS: Robert Henschel
  • IU Biology: Michael Lynch

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Last modified on 2018-01-18 17:09:59.