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. 2019 Apr 10;9(6):1851–1867. doi: 10.1534/g3.119.400088

Table 1. Explanation of terms used in this study.

Term Description
Genome scan A statistical test used to infer the genetic loci either affected by selection or that affect a trait
Test statistic The numerical summary calculated for each locus that reduces the data to one value that can be used to perform the hypothesis test. The relationship between the test statistic and the P-value for that test statistic depends on the shape of the distribution used to model the null hypothesis (e.g., neutral parameterization).
Quantitative trait nucleotide (QTN) A causal allele that has an additive effect on a quantitative trait
Linkage disequilibrium (LD) Non-random association of alleles at different loci
Neutral parameterization The process of calibrating or calculating the distribution of the test statistic expected under neutrality (i.e., the neutral demographic process)
Neutral parameterization with all SNPs and genome scan on all SNPs (“naive”) When based on all SNPs, neutral parameterization may be biased due to non-independence among SNPs due to linkage disequilibrium. Since this is the default for many programs, it is referred to as the “naive” approach. But note that for some genome scans, this is the only option.
LD thinning, SNP thinning, thinned SNPs Move along a genome in a sliding window and reduce the set of SNPs to those that have reduced linkage disequilibrium with each other
Neutral parameterization with thinned SNPs and genome scan on thinned SNPs When based on a set of SNPs thinned for LD, neutral parameterization is less likely to be biased due to linkage disequilibrium among SNPs. However, trimming removes many causal SNPs, and can greatly reduce the probability of finding causal SNPs in the genome scan. For this reason, this approach was not evaluated.
Neutral parameterization with thinned SNPs and genome scan on all SNPs (“best practice”) Neutral parameterization on a set of thinned SNPs is less likely to be biased due to linkage disequilibrium among SNPs. This parameterization can then be used when performing the genome scan on the entire set of SNPs.