Optimizing genotype quality metrics for individual exomes and cohort analysis

Background Few evidence-based best practice bioinformatics guidelines exist for genotyping using next-generation sequencing data, especially colorspace data produced by Life Technologies sequencers. Dozens of software packages can perform the various steps required, and genome features such as pseudogenes or large paralogous gene families are problematic. High false positive and negative rates can compound the difficulty of cohort analysis.