Author: Pandya, Gagan A.; Holmes, Michael H.; Sunkara, Sirisha; Sparks, Andrew; Bai, Yun; Verratti, Kathleen; Saeed, Kelly; Venepally, Pratap; Jarrahi, Behnam; Fleischmann, Robert D.; Peterson, Scott N.
Title: A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChip® whole-genome resequencing platform Document date: 2007_11_15
ID: 16tii0ha_45
Snippet: Systematic effects causing false-positive SNP calls in the resequencing platform are exacerbated by the hybridization of a whole-genome sample, as compared with a sample consisting of purified selected PCR fragments. A whole-genome sample contains a much larger complexity of targets for hybridization than does a PCR-amplified subset of the whole genome, and these additional targets give rise to some of the inaccurate base calls. The widely accept.....
Document: Systematic effects causing false-positive SNP calls in the resequencing platform are exacerbated by the hybridization of a whole-genome sample, as compared with a sample consisting of purified selected PCR fragments. A whole-genome sample contains a much larger complexity of targets for hybridization than does a PCR-amplified subset of the whole genome, and these additional targets give rise to some of the inaccurate base calls. The widely accepted ABACUS algorithm (4) for the Affymetrix-based resequencing platform may not perform with equal efficiency on a whole-genome query sample. It is necessary to understand the nature and source of errors in whole-genome hybridization in order to optimally use this platform. Improved base-calling algorithms and bioinformatic tools are essential to decrease false positives, minimize false negatives and increase the overall base-calling accuracy of this platform. The bioinformatic filters reported here were developed towards achieving these goals.
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