Automated SNP Genotype Clustering Algorithm to Improve Data Completeness in High-Throughput SNP Genotyping Datasets from Custom Arrays
- Author:
Smith M. EDWARD
1
;
Littrell JACK
;
Olivier MICHAEL
Author Information
1. Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, WI 53226, USA
- Keywords:
clustering;
SNP geuotyping;
algorithm
- From:
Genomics, Proteomics & Bioinformatics
2007;2(3):256-259
- CountryChina
- Language:Chinese
-
Abstract:
High-throughput SNP genotyping platforms use automated genotype calling algo- rithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been opti- mized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be ad- visable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author.
