Viability of in-house datamarting approaches for population genetics analysis of snp genotypes

ABSTRACT

Databases containing very large amounts of SNP (Single Nucleotide Polymorphism) data are now freely available for researchers interested in medical or population genetics applications. While many of these SNP repositories have implemented data retrieval tools for general purpose mining, these alone cannot cover the broad spectrum of needs of most medical and population genetics studies. To address this limitation, we propose building in-house customized data marts from the raw data provided by the largest public databases. In particular, for population genetics analysis based on genotypes we propose building a set of data processing scripts that would deal with raw data coming from the major SNP variation databases (e.g. HapMap, Perlegen) that can be stripped into single genotypes and then grouped into populations. This allows not only in-house standardization and normalization of the genotyping data retrieved from different repositories, but also the calculation of statistical indices from simple allele frequency estimates up to elaborate genetic differentiation tests within populations, together with the ability to combine population samples from different databases. This article describes the viability of implementing scripts for handling extensive datasets of SNP genotypes with low computational costs, and shows that the updating of these data marts is straightforward, permitting easy implementation of new external data and the computation of new statistical indices.

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INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.3 LIFE AND MEDICAL SCIENCES
      Subjects: Biology and genetics

General Terms:
Design, Management, Performance, Reliability, Standardization, Verification

Keywords:
ceph, data mart, genotypes, hapmap, perlegen, population genetics, snps