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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)