title: Genetic Analysis Workshop 18 single-nucleotide variant prioritization based on protein impact, sequence conservation, and gene annotation.
abstract: Grouping variants based on gene mapping can augment the power of rare variant association tests. Weighting or sorting variants based on their expected functional impact can provide additional benefit. We defined groups of prioritized variants based on systematic annotation of Genetic Analysis Workshop 18 (GAW18) single-nucleotide variants; we focused on variants detected by whole genome sequencing, specifically on the high-quality subset presented in the genotype files. First, we divided variants between coding and noncoding. Coding variants are fewer than 1% of the total and are more likely to have a biological effect than noncoding variants. Coding variants were further stratified into protein changing and protein damaging groups based on the effect on protein amino acid sequence. In particular, missense variants predicted to be damaging, splice-site alterations, and stop gains were assigned to the protein damaging category. Impact of noncoding variants is more difficult to predict. We decided to rely uniquely on conservation: we combined (a) the mammalian phastCons Conserved Element and (b) the PhyloP score, which identify conserved intervals and the single-nucleotide position, respectively. This reduced the noncoding variants to a number comparable to coding variants. Finally, using gene structure definition from the widely used RefSeq database, we mapped variants to genes to support association tests that require collapsing rare variants to genes. Companion GAW18 papers used these variant priority groups and gene mapping; one of these paper specifically found evidence of stronger association signal for protein damaging variants.
authors.affiliation: The Centre for Applied Genomics, The Hospital for Sick Children, 101 College Street, M5G 1L7 Toronto, ON, Canada ; Program in Genetics and Genome Biology, The Hospital for Sick Children, 101 College Street, M5G 1L7 Toronto, ON, Canada.
authors.forename: Thomas
authors.initials: T
authors.lastname: Nalpathamkalam
authors.affiliation: Department of Statistics, University of Toronto, 100 St. George St., M5S 3G3 Toronto, ON, Canada.
authors.forename: Andriy
authors.initials: A
authors.lastname: Derkach
authors.affiliation: Program in Genetics and Genome Biology, The Hospital for Sick Children, 101 College Street, M5G 1L7 Toronto, ON, Canada ; Division of Biostatistics, Dalla Lana School of Public Health, 155 College Street, University of Toronto, M5T 3M7 Toronto, ON, Canada.
authors.forename: Andrew D
authors.initials: AD
authors.lastname: Paterson
authors.affiliation: The Centre for Applied Genomics, The Hospital for Sick Children, 101 College Street, M5G 1L7 Toronto, ON, Canada ; Program in Genetics and Genome Biology, The Hospital for Sick Children, 101 College Street, M5G 1L7 Toronto, ON, Canada.
authors.forename: Daniele
authors.initials: D
authors.lastname: Merico