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Table 1 Comparison of core subsets selected by MSTRAT, D-Method and Core Hunter

From: Core Hunter: an algorithm for sampling genetic resources based on multiple genetic measures

Strategy MR CE SH HE NE PN CV
  Bulk data set
Core Hunter (single)† 0.572 0.641 4.531 0.667 3.446 0.000 100.000
Core Hunter (multi)‡ 0.506 0.598 4.513 0.662 3.403 0.015 98.500
MSTRAT 0.477 0.571 4.493 0.649 3.217 0.021 97.900
D-Method§ 0.503 0.578 4.411 0.626 2.980 0.066 93.400
COLLECTION 0.440 0.521 4.399 0.620 2.937 0.000 100.000
  Accession data set
Core Hunter (single)† 0.694 0.752 4.670 0.676 3.501 0.000 100.000
Core Hunter (multi)‡ 0.659 0.733 4.613 0.650 3.281 0.084 91.600
MSTRAT 0.647 0.718 4.579 0.624 2.982 0.000 100.000
D-Method§ 0.653 0.719 4.525 0.619 2.963 0.164 83.600
COLLECTION 0.630 0.696 4.467 0.591 2.742 0.000 100.000
  Population data set
Core Hunter (single)† 0.442 0.540 4.503 0.619 2.997 0.177 82.300
Core Hunter (multi)‡ 0.396 0.508 4.482 0.609 2.969 0.225 77.500
MSTRAT 0.357 0.465 4.450 0.593 2.763 0.183 81.700
D-Method§ 0.377 0.485 4.409 0.579 2.702 0.264 73.600
COLLECTION 0.357 0.455 4.466 0.592 2.749 0.000 100.000
  1. †each selection criteria was attempted to be optimized independently by performing 20 runs with 100% weight given to the respective selection criteria during each run. Results reported for each measure are independent of results reported for all other measures.
  2. ‡20 independent runs were performed with equal weight given to each of the seven measures in an attempt to maximize (minimize) all measures simultaneously.
  3. §for each measure, results are shown for the best performing strategy as reported in [9].