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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].