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Table 3 Top standard methodologies and performance of VI-cut.

From: Alignment and clustering of phylogenetic markers - implications for microbial diversity studies

MSA Clustering Distance mean VI
MUSCLE VI-cut adaptive 0.0589
ClustalW VI-cut adaptive 0.0595
ClustalW fn 0.03 0.0688
MUSCLE fn 0.04 0.0691
ClustalW fn 0.04 0.0697
MUSCLE fn 0.05 0.0748
NAST VI-cut adaptive 0.0762
ClustalW fn 0.02 0.0838
NAST fn 0.05 0.0845
MUSCLE fn 0.03 0.0860
NAST fn 0.06 0.0872
ClustalW fn 0.05 0.0942
NAST fn 0.04 0.0992
MUSCLE fn 0.06 0.1025
ClustalW fn 0.06 0.1176
NAST fn 0.03 0.1222
MUSCLE fn 0.02 0.1370
ClustalW fn 0.01 0.1505
NAST fn 0.02 0.1633
NAST fn 0.01 0.2362
MUSCLE fn 0.01 0.2629
  1. Methods are ranked by their mean VI-distance over 10 simulated datasets. We constrained the results to commonly accepted methods using furthest neighbor clustering and distance thresholds less than 0.07. A distance threshold of 0.01 is consistently among the worst performing methodologies. VI-cut consistently results in the best clustering for each MSA.