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Using Mata to import Illumina SNP chip data for genome-wide association studies

Author

Listed:
  • J. Charles Huber Jr.

    (Texas A&M University)

  • Michael Hallman
  • Victoria Friedel
  • Melissa Richard
  • Huandong Sun

Abstract

Modern genetic genome-wide association studies typically rely on single nucleotide polymorphism (SNP) chip technology to determine hundreds of thousands of genotypes for an individual sample. Once these genotypes are ascertained, each SNP alone or in combination is tested for association outcomes of interest such as disease status or severity. Project Heartbeat! was a longitudinal study conducted in the 1990s that explored changes in lipids and hormones and morphological changes in children from 8 to 18 years of age. A genome-wide association study is currently being conducted to look for SNPs that are associated with these developmental changes. While there are specialty programs available for the analysis of hundreds of thousands of SNPs, they are not capable of modeling longitudinal data. Stata is well equipped for modeling longitudinal data but cannot load hundreds of thousands of variables into memory simultaneously. This talk will briefly describe the use of Mata to import hundreds of thousands of SNPs from the Illumina SNP chip platform and how to load those data into Stata for longitudinal modeling.

Suggested Citation

  • J. Charles Huber Jr. & Michael Hallman & Victoria Friedel & Melissa Richard & Huandong Sun, 2011. "Using Mata to import Illumina SNP chip data for genome-wide association studies," United Kingdom Stata Users' Group Meetings 2011 16, Stata Users Group.
  • Handle: RePEc:boc:usug11:16
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