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Hum Genet. 2012 Oct;131(10):1541-54. doi: 10.1007/s00439-012-1213-z. Epub 2012 Aug 11.

A beginners guide to SNP calling from high-throughput DNA-sequencing data.

Author information

1
Statistical Genetics, Max Planck Institute of Psychiatry, Kraepelinstrasse 2-10, 80804 Munich, Germany. altmann@stanford.edu

Abstract

High-throughput DNA sequencing (HTS) is of increasing importance in the life sciences. One of its most prominent applications is the sequencing of whole genomes or targeted regions of the genome such as all exonic regions (i.e., the exome). Here, the objective is the identification of genetic variants such as single nucleotide polymorphisms (SNPs). The extraction of SNPs from the raw genetic sequences involves many processing steps and the application of a diverse set of tools. We review the essential building blocks for a pipeline that calls SNPs from raw HTS data. The pipeline includes quality control, mapping of short reads to the reference genome, visualization and post-processing of the alignment including base quality recalibration. The final steps of the pipeline include the SNP calling procedure along with filtering of SNP candidates. The steps of this pipeline are accompanied by an analysis of a publicly available whole-exome sequencing dataset. To this end, we employ several alignment programs and SNP calling routines for highlighting the fact that the choice of the tools significantly affects the final results.

PMID:
22886560
DOI:
10.1007/s00439-012-1213-z
[Indexed for MEDLINE]

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