Genetic simulation tools for post-genome wide association studies of complex diseases

Huann-Sheng Chen^#¹, Carolyn M Hutter^#², Leah E Mechanic^#³, Christopher I Amos⁴, Vineet Bafna⁵, Elizabeth R Hauser⁶, Ryan D Hernandez⁷, Chun Li⁸, David A Liberles⁹, Kimberly McAllister¹⁰, Jason H Moore¹¹, Dina N Paltoo¹², George J Papanicolaou¹³, Bo Peng¹⁴, Marylyn D Ritchie¹⁵, Gabriel Rosenfeld¹, John S Witte¹⁶, Elizabeth M Gillanders^#³, Eric J Feuer^#¹

Affiliations

¹ Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892.
² Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD 20892.
³ Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892.
⁴ Division of Community, Family Medicine, Dartmouth College, Lebanon, NH 03755.
⁵ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093.
⁶ Duke Molecular Physiology Institute, Duke University, Durham, NC 27710.
⁷ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94143.
⁸ Department of Biostatistics, Vanderbilt University, Nashville, TN 37235.
⁹ Department of Molecular Biology, University of Wyoming, Laramie, WY 82071.
¹⁰ Susceptibility and Population Health Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709.
¹¹ Department of Genetics, Dartmouth College, Lebanon, NH 03755.
¹² Office of Director, National Institutes of Health, Bethesda, MD 20892.
¹³ Division of Cardiovascular Sciences, Prevention and Population Sciences Program, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892.
¹⁴ Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030.
¹⁵ Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802.
¹⁶ Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94107.

^# Contributed equally.

PMID: 25371374
PMCID: PMC4270837
DOI: 10.1002/gepi.21870

Genetic simulation tools for post-genome wide association studies of complex diseases

Huann-Sheng Chen et al. Genet Epidemiol. 2015 Jan.

. 2015 Jan;39(1):11-19.

doi: 10.1002/gepi.21870. Epub 2014 Nov 4.

Authors

Affiliations

¹ Surveillance Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892.
² Division of Genomic Medicine, National Human Genome Research Institute, NIH, Bethesda, MD 20892.
³ Epidemiology and Genomics Research Program, Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, MD 20892.
⁴ Division of Community, Family Medicine, Dartmouth College, Lebanon, NH 03755.
⁵ Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92093.
⁶ Duke Molecular Physiology Institute, Duke University, Durham, NC 27710.
⁷ Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94143.
⁸ Department of Biostatistics, Vanderbilt University, Nashville, TN 37235.
⁹ Department of Molecular Biology, University of Wyoming, Laramie, WY 82071.
¹⁰ Susceptibility and Population Health Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC 27709.
¹¹ Department of Genetics, Dartmouth College, Lebanon, NH 03755.
¹² Office of Director, National Institutes of Health, Bethesda, MD 20892.
¹³ Division of Cardiovascular Sciences, Prevention and Population Sciences Program, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892.
¹⁴ Department of Bioinformatics and Computational Biology, University of Texas MD Anderson Cancer Center, Houston, TX 77030.
¹⁵ Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA 16802.
¹⁶ Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94107.

^# Contributed equally.

PMID: 25371374
PMCID: PMC4270837
DOI: 10.1002/gepi.21870

Abstract

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.

Keywords: complex phenotypes; computational resources; genetic simulation; next-generation sequencing; rare variants.

PubMed Disclaimer

References

1. Agarwala V, Flannick J, Sunyaev S, Altshuler D. Evaluating empirical bounds on complex disease genetic architecture. Nat Genet. 2013;45(12):1418–27. - PMC - PubMed
1. Beaumont MA, Zhang W, Balding DJ. Approximate Bayesian computation in population genetics. Genetics. 2002;162(4):2025–35. - PMC - PubMed
1. Caro JJ, Briggs AH, Siebert U, Kuntz KM. Modeling good research practices--overview: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-1. Med Decis Making. 2012;32(5):667–77. - PubMed
1. Chen H, Yu T, Chen JY. Semantic Web meets Integrative Biology: a survey. Brief Bioinform. 2013;14(1):109–25. - PubMed
1. Coventry A, Bull-Otterson LM, Liu X, Clark AG, Maxwell TJ, Crosby J, Hixson JE, Rea TJ, Muzny DM, Lewis LR, Wheeler DA, Sabo A, Lusk C, Weiss KG, Akbar H, Cree A, Hawes AC, Newsham I, Varghese RT, Villasana D, Gross S, Joshi V, Santibanez J, Morgan M, Chang K, Iv WH, Templeton AR, Boerwinkle E, Gibbs R, Sing CF. Deep resequencing reveals excess rare recent variants consistent with explosive population growth. Nat Commun. 2010;1:131. - PMC - PubMed

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Grants and funding

LinkOut - more resources

Full Text Sources
Other Literature Sources
- scite Smart Citations

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Genetic simulation tools for post-genome wide association studies of complex diseases

Affiliations

Genetic simulation tools for post-genome wide association studies of complex diseases

Authors

Affiliations

Abstract

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources