title: PGRNseq: a targeted capture sequencing panel for pharmacogenetic research and implementation.
abstract: OBJECTIVE
  Although the costs associated with whole-genome and whole-exome next-generation sequencing continue to decline, they remain prohibitively expensive for large-scale studies of genetic variation. As an alternative, custom-target sequencing has become a common methodology on the basis of its favorable balance between cost, throughput, and deep coverage.
  
  
  METHODS
  We have developed PGRNseq, a custom-capture panel of 84 genes with associations to pharmacogenetic phenotypes, as a tool to explore the relationship between drug response and genetic variation, both common and rare. We utilized a set of 32 diverse HapMap trios and two clinical cohorts to assess platform performance, accuracy, and ability to discover novel variation.
  
  
  RESULTS
  We found that PGRNseq generates ultra-deep coverage data (mean=496x) that are over 99.8% concordant with orthogonal datasets. In addition, in our testing sets, PGRNseq identified many novel, rare variants of interest, underscoring its value in both research and clinical settings.
  
  
  CONCLUSIONS
  PGRNseq is an ideal platform for carrying out sequencing-based analyses of pharmacogenetic variation in large cohorts. In addition, the high accuracy associated with genotypes from PGRNseq highlight its utility as a clinical test.
authors.affiliation: aDepartment of Genome Sciences, University of Washington, Seattle, Washington bThe Baylor College of Medicine Human Genome Sequencing Center, Houston, Texas cThe Genome Institute at Washington University, St Louis, Missouri, USA.
authors.forename: Adam S
authors.initials: AS
authors.lastname: Gordon
authors.forename: Robert S
authors.initials: RS
authors.lastname: Fulton
authors.forename: Xiang
authors.initials: X
authors.lastname: Qin
authors.forename: Elaine R
authors.initials: ER
authors.lastname: Mardis
authors.forename: Deborah A
authors.initials: DA
authors.lastname: Nickerson
authors.forename: Steve
authors.initials: S
authors.lastname: Scherer