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.

overnight run in this environment. However, this time can typically be reduced to less than 1 h if a precomputed database of binding energies is used. The most computationally intensive part of the filter algorithms is the identification of potential alternate homologies in the reference sequence, and the calculation of binding energies for these sequences. But this task need only be performed the first time that a particular SNP location is encountered. We store the results of these calculations in a data file, and when new experiments are processed, results for previously encountered SNP locations are looked up in this database rather than computed. Some of the issues identified in our results suggest some areas for further improvement of our filters. The presence of false-positive SNP calls that occur near rearrangement boundaries indicates that the low-homology filter did not identify all low-homology regions that could potentially be removed, and its performance could be further improved. Identifying a signature in the resequencing data that corresponds to a rearrangement boundary may allow us to filter false-positive SNPs from this source. More importantly, this boundary information itself should prove to be a valuable tool for the genotyping of different strains of an organism. The occurrence of coincident rearrangement boundaries in two different samples is strong evidence of genetic similarity and can be used in conjunction with the SNP data to draw conclusions about phylogenetic relationships.