A bioinformatic filter for improved base-call accuracy and polymorphism detection using the Affymetrix GeneChip® whole-genome resequencing platform

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.

The raw whole-genome resequencing data, even though apparently acceptable, has a rather large number of false positives (Table 2) , indicating an inherent limitation of the existing data analysis tool on the Affymetrix resequencing platform. We have developed a set of software filters to identify and filter out SNP calls that are likely to be artifacts. These filters operate on the base calls and quality scores provided by the Affymetrix GSEQ program, yielding a set of high-confidence SNP calls containing a lower percentage of false positives. We used the set of SNPs predicted by in silico analysis for the hybridization of the SCHU S4 sample to test and fine-tune our filters. Our bioinformatic filters identified many of these false positives ( Table 3) .