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Table 3 Medium-gap-length model conditions: estimated alignment statistics

From: Non-parametric and semi-parametric support estimation using SEquential RESampling random walks on biomolecular sequences

Model conditionEst align lengthSP-FNSP-FP
MAFFT
10.A1552.30.2940.341
10.B1563.50.4830.533
10.C1554.00.6570.684
10.D1507.50.7470.752
10.E1612.80.9450.943
50.A1785.70.0860.088
50.B1714.20.1050.102
50.C1703.10.2450.230
50.D1712.20.4550.419
50.E2319.20.9630.948
Model conditionEst align lengthSP-FNSP-FP
ClustalW
10.A1208.50.4970.556
10.B1186.20.6240.684
10.C1144.80.7110.754
10.D1105.70.7560.786
10.E1060.10.8960.906
Model conditionEst align lengthSP-FNSP-FP
FSA
10.A2289.30.3340.124
10.B3418.50.5850.164
10.C4506.60.7290.211
10.D5000.90.8000.223
10.E6657.10.9070.531
  1. The MSA support estimation problem requires an input MSA. MAFFT [9] was used to estimate an input MSA for all model conditions in our study. Our study also included ClustalW [13] and FSA [2] alignments to explore the impact of input alignment quality on downstream support estimation. The following table columns list average statistics for estimated alignments on each model condition (\(n=20\)). “Est align length” is the estimated alignment length. “SP-FN” and “SP-FP” are the proportion of homologies that appear in the true alignment but not in the estimated alignment and vice versa, respectively