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Table 1 Topological accuracy with medium-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

0.0841

0.0906

0.0926

0.0841

0.0857

0.286

4

0.0504

0.0546

0.0595

0.0494

0.0524

0.466

6

0.0400

0.0445

0.0454

0.0370

0.0410

0.015

8

0.0330

0.0356

0.0386

0.0318

0.0320

0.958

10

0.0271

0.0300

0.0317

0.0265

0.0286

0.364

12

0.0294

0.0317

0.0354

0.0284

0.0314

0.030

14

0.0245

0.0266

0.0286

0.0235

0.0251

0.816

16

0.0290

0.0318

0.0327

0.0282

0.0303

0.028

18

0.0252

0.0278

0.0280

0.0234

0.0265

0.020

20

0.0242

0.0259

0.0281

0.0230

0.0247

0.955

(b): 75% taxon deletion rate

k=

FITCH

MW*

NJ*

BIONJ*

MVR*

p -value

2

0.2154

0.2174

0.2187

0.2131

0.2163

0.920

4

0.1683

0.1778

0.1818

0.1713

0.1713

0.060

6

0.1347

0.1443

0.1534

0.1418

0.1400

≈ 0.0

8

0.1089

0.1253

0.1302

0.1137

0.1114

0.176

10

0.0878

0.1039

0.1117

0.0959

0.0901

0.033

12

0.0825

0.0968

0.1021

0.0875

0.0842

0.470

14

0.0652

0.0749

0.0850

0.0710

0.0676

0.464

16

0.0583

0.0731

0.0802

0.0658

0.0625

0.335

18

0.0516

0.0617

0.0687

0.0552

0.0555

0.074

20

0.0503

0.0600

0.0682

0.0560

0.0509

0.189

  1. In the medium-level combination, distance matrices are directly estimated from each of the genes and then combined (using SDM) into the distance supermatrix. Topolological accuracy is mesured by the mean (over 500 trials) quartet distance (d q ) between the correct and inferred trees. k: number of genes. p-value: sign-test significance when comparing the 500 d q values of the two best methods that are indicated in bold and underlined (1st method) and bold (2nd one)
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BMC Bioinformatics

ISSN: 1471-2105

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