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Table 2 Description of BayesRC models used to analyse the SEQ a genotype data

From: Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

Name of BayesRC Model Variant Allocation to Classes I, II and III Number of variants per classc
BayesRC Seq I. NSC (non-synonymous coding)
II. REG (potentially regulatory)
III. CHIP (HD SNP chip variants)
BayesRC Lact I. NSC & in Lact b genes
II. All variants other than NSC that overlap Lact gene regions (±50Kb)
III. All other SEQ variants not in class I or II
BayesRC RLact I. NSC & in random set of 790 genes
II. Variants other than NSC that overlap a random set of 790 genes (±50Kb)
III. All other variants not in class I or II
  1. aSEQ = pruned set of 994,019 genome-wide sequence variants from coding and regulatory regions as well as SNP from a high density genotyping array. Variants were allocated to one of three BayesRC classes as listed
  2. bLact refers to a set of 790 candidate genes shown in an independent study to be differentially expressed in association with altered milk production
  3. cNumbers generally reduced slightly from those listed because variants with MAF < 0.002 in any given training population were also excluded from the analyses