Genetic Simulation Resources and the GSR Certification Program

Bo Peng, Man Chong Leong, Huann Sheng Chen, Melissa Rotunno, Katy R. Brignole, John Clarke, Leah E. Mechanic

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

With recent explosion in the diversity and volume of genetic data generated, an increasing number of genetic simulation programs have been developed to aid the development of statistical methods for the analysis of such data in all genetic-related disciplines (Escalona et al., 2016; Hoban et al., 2012; Peng et al., 2015; Ritchie and Bush, 2010). Despite the recognized importance of genetic simulation tools, it is often difficult to discover and select the right simulation tool for a particular study due to differences in the type of genetic data of interest, simulation methods, features, terminologies and assumptions (Mechanic et al., 2012), and lack of external evaluations of the usability and maintenance status of published simulators. To address these issues, we want to encourage use of the Genetic Simulation Resources (GSR) online catalog and search tool (https://popmodels.cancercontrol.cancer.gov/gsr/) and participation in the GSR Certification Program.

Original languageEnglish (US)
Pages (from-to)709-710
Number of pages2
JournalBioinformatics
Volume35
Issue number4
DOIs
StatePublished - Feb 15 2019

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

MD Anderson CCSG core facilities

  • Bioinformatics Shared Resource

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