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Table 2 Topological accuracy with high-level distance supermatrices

From: Fast NJ-like algorithms to deal with incomplete distance matrices

(a): 25% taxon deletion rate

k=

FITCH

MW*

NJ*

BIONJ*

MVR*

p -value

2

0.0558

0.0561

0.0586

0.0566

0.0522

≈ 0.0

4

0.0337

0.0345

0.0361

0.0351

0.0319

≈ 0.0

6

0.0253

0.0265

0.0272

0.0261

0.0235

≈ 0.0

8

0.0227

0.0228

0.0213

0.0217

0.0212

0.094

10

0.0187

0.0188

0.0194

0.0192

0.0171

0.047

12

0.0197

0.0207

0.0215

0.0199

0.0191

0.949

14

0.0160

0.0164

0.0164

0.0165

0.0162

0.882

16

0.0208

0.0204

0.0210

0.0213

0.0206

≈ 0.0

18

0.0170

0.0177

0.0177

0.0173

0.0174

0.271

20

0.0162

0.0168

0.0171

0.0160

0.0158

0.648

(b): 75% taxon deletion rate

k=

FITCH

MW*

NJ*

BIONJ*

MVR*

p -value

2

0.1876

0.1877

0.1824

0.1822

0.1817

0.282

4

0.1396

0.1397

0.1390

0.1381

0.1345

0.018

6

0.1095

0.1125

0.1134

0.1119

0.1065

0.166

8

0.0865

0.0892

0.0926

0.0870

0.0823

0.005

10

0.0690

0.0739

0.0766

0.0723

0.0671

0.023

12

0.0641

0.0670

0.0705

0.0677

0.0616

0.015

14

0.0508

0.0538

0.0567

0.0534

0.0493

≈ 0.0

16

0.0504

0.0518

0.0554

0.0512

0.0457

≈ 0.0

18

0.0409

0.0416

0.0485

0.0424

0.0402

0.922

20

0.0403

0.0435

0.0453

0.0431

0.0371

≈ 0.0

  1. In the high-level combination, ML trees are first inferred separately for every genes, and then these trees are turned into path-length distance matrices which are combined (using SDM) into the distance supermatrix. For symbols and notation, see note to Table 1.