Table 2.
Correlations between Rogers’ distance matrices of the individual lines of the test population
Data set | Ref 50 | Ref 100 | Ref 200 | Ref 300 |
---|---|---|---|---|
cor | cor | cor | cor | |
9 k panel | 0.95 | 0.95 | 0.95 | 0.95 |
Beagle | 0.83 | 0.92 | 0.95 | 0.96 |
FImpute | 0.95 | 0.96 | 0.97 | 0.97 |
IMPUTE2 | 0.96 | 0.97 | 0.98 | 0.98 |
Random Forest | 0.61 | 0.61 | 0.61 | 0.66 |
Estimates are based solely on imputed parts of data sets (90 k SNP minus 9 k SNP data) and the original 90 k SNP data set, as well as the correlation between Rogers’ distance matrices of the original 9 k and original 90 k SNP data sets. Different imputed low to high marker density data sets were generated by map- dependent (Beagle, FImpute, and IMPUTE2) and map-independent (Random Forest) imputation algorithms for reference populations of 50, 100, 200, and 300 out of 371 lines. All correlations were significantly larger than zero (P < 0.01) according to a Mantel test.