title: Choosing Subsamples for Sequencing Studies by Minimizing the Average Distance to the Closest Leaf.
abstract: Imputation of genotypes in a study sample can make use of sequenced or densely genotyped external reference panels consisting of individuals that are not from the study sample. It also can employ internal reference panels, incorporating a subset of individuals from the study sample itself. Internal panels offer an advantage over external panels because they can reduce imputation errors arising from genetic dissimilarity between a population of interest and a second, distinct population from which the external reference panel has been constructed. As the cost of next-generation sequencing decreases, internal reference panel selection is becoming increasingly feasible. However, it is not clear how best to select individuals to include in such panels. We introduce a new method for selecting an internal reference panel--minimizing the average distance to the closest leaf (ADCL)--and compare its performance relative to an earlier algorithm: maximizing phylogenetic diversity (PD). Employing both simulated data and sequences from the 1000 Genomes Project, we show that ADCL provides a significant improvement in imputation accuracy, especially for imputation of sites with low-frequency alleles. This improvement in imputation accuracy is robust to changes in reference panel size, marker density, and length of the imputation target region.
authors: Department of Biology, Stanford University, Stanford, California 94305 jtlkang@stanford.edu.
authors: Jonathan T L
authors: JT
authors: Kang
authors: Center for Inherited Disease Research, Johns Hopkins University, Baltimore, Maryland 21224.
authors: Peng
authors: P
authors: Zhang
authors: Departments of Biostatistics and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109.
authors: Sebastian
authors: S
authors: Zöllner
authors: Department of Biology, Stanford University, Stanford, California 94305.
authors: Noah A
authors: NA
authors: Rosenberg
mesh_terms: D000465:Algorithms; D000483:Alleles; D003198:Computer Simulation; D014644:Genetic Variation; D005838:Genotype; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D016045:Human Genome Project; D006801:Humans; D010802:Phylogeny; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012984:Software
keywords: algorithms; imputation; polymorphic sites; sequencing; study design