Concordance analysis implied calculation of specificity, sensitivity, precision, accuracy, genotype concordance, non-reference genotype concordance and non-reference sensitivity of genotyping between BeadChip and WGS. The analysis implemented confusion matrices calculation (Fig. 6). As there is no baseline “truth” when a WGS call set is compared with a BeadChip one, no method can be described as “comparator”. Because of this, each call set within each pair was treated as alternating “truth” or “test” call set, followed by the averaging of obtained statistics. Filling those matrices with observed numbers of class counts was followed by dimensionality reduction, which implied leaving one class in both call sets intact and combining the counts in all other classes (Fig. 6). The above-specified quality metrics for the initial and reduced matrices were calculated, as shown in Fig. 7 [2] with amendments. As each non-reduced matrix produced 6 submatrices, the calculated sensitivity and precision value for each submatrix was weighted by the fraction of analyzed elements in a non-reduced matrix (i.e., each calculated metric was then multiplied by the ratio of orange-outlined elements to all elements in the
