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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.