In:
PLOS Genetics, Public Library of Science (PLoS), Vol. 17, No. 6 ( 2021-6-4), p. e1009534-
Abstract:
Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.
Type of Medium:
Online Resource
ISSN:
1553-7404
DOI:
10.1371/journal.pgen.1009534
DOI:
10.1371/journal.pgen.1009534.g001
DOI:
10.1371/journal.pgen.1009534.g002
DOI:
10.1371/journal.pgen.1009534.g003
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10.1371/journal.pgen.1009534.g004
DOI:
10.1371/journal.pgen.1009534.g005
DOI:
10.1371/journal.pgen.1009534.g006
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10.1371/journal.pgen.1009534.g007
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10.1371/journal.pgen.1009534.g008
DOI:
10.1371/journal.pgen.1009534.g009
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10.1371/journal.pgen.1009534.g010
DOI:
10.1371/journal.pgen.1009534.g011
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10.1371/journal.pgen.1009534.g012
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10.1371/journal.pgen.1009534.g013
DOI:
10.1371/journal.pgen.1009534.t001
DOI:
10.1371/journal.pgen.1009534.t002
DOI:
10.1371/journal.pgen.1009534.t003
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10.1371/journal.pgen.1009534.s001
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10.1371/journal.pgen.1009534.s002
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10.1371/journal.pgen.1009534.s003
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10.1371/journal.pgen.1009534.s004
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10.1371/journal.pgen.1009534.s005
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10.1371/journal.pgen.1009534.s006
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10.1371/journal.pgen.1009534.s007
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10.1371/journal.pgen.1009534.s008
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10.1371/journal.pgen.1009534.s009
DOI:
10.1371/journal.pgen.1009534.s010
DOI:
10.1371/journal.pgen.1009534.s011
DOI:
10.1371/journal.pgen.1009534.s012
DOI:
10.1371/journal.pgen.1009534.s013
DOI:
10.1371/journal.pgen.1009534.s014
DOI:
10.1371/journal.pgen.1009534.s015
DOI:
10.1371/journal.pgen.1009534.s016
DOI:
10.1371/journal.pgen.1009534.r001
DOI:
10.1371/journal.pgen.1009534.r002
DOI:
10.1371/journal.pgen.1009534.r003
DOI:
10.1371/journal.pgen.1009534.r004
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2021
detail.hit.zdb_id:
2186725-2
