Dropping imputation for missing genotypes results in an even higher (r = 0.73) for correlation with the fraction of missing data.
We were not able to detect interaction between ScIce2 and ScCbf9b probably due to the large number of rare haplotypes (MAF < 5%) in ScCbf9b resulting in missing genotypes (87.9%) and thus in insufficient statistical power to identify gene × gene interaction.
Pilot participants with inconsistent calls across methods were assigned 'no call' at the SNP, which resulted in 2 missing genotypes at mt204 and 1 at mt228.
To maximize our sample size without adding uncertainty, we evaluated the effect of missing genotypes on individual assignment test results.
Recently, however, Thallman et al. [ 40] developed a recursive formula that gives exact results with missing genotypes for a pedigree with loops.
However, MDA is more sensitive to DNA quality and quantity as well as stochastic effects, leading to reduced genome coverage which in turn results in missing genotypes and allele dropout at heterozygous loci [ 38, 39].
This has resulted in high rates of missing genotypes (assay fail rates of 21%), incomplete genotypes (64% of loci departing from HWE) and inaccurate genotypes (1% of genotypes inconsistent across replicates).
Only SNPs with less than 5% missing genotypes and minor allele frequency greater than 3% were used, resulting in 40,588 SNPs.
Even with up to 5% missing genotypes or 0.2% genotyping error rate, SLRP results in several fold fewer switch errors than the general purpose methods.
