Review

Nature Reviews Genetics 12, 443-451 (June 2011) | doi:10.1038/nrg2986

Article series: Study designs

Genotype and SNP calling from next-generation sequencing data

Rasmus Nielsen1,2,3, Joshua S. Paul4, Anders Albrechtsen2 & Yun S. Song3,4  About the authors

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Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data. We review these methods and provide a guide for their use in NGS studies.

Author affiliations

  1. Department of Integrative Biology, University of California, Berkeley, California 94720, USA.
  2. Centre for Bioinformatics, University of Copenhagen, Universitetsparken 15, 2100 Copenhagen Ø, Denmark.
  3. Department of Statistics, University of California, Berkeley, California 94720, USA.
  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California 94720, USA.

Correspondence to: Rasmus Nielsen1,2,3 Email: rasmus_nielsen@berkeley.edu

Correspondence to: Yun S. Song3,4 Email: yss@stat.berkeley.edu

Published online 18 May 2011