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Table 5 False positive rates for 500-taxon model conditions

From: MRL and SuperFine+MRL: new supertree methods

 

Scaffold Density

Method

20

50

75

100

Average

MRP(PAUP*)

22.1 (1.0)

18.8 (0.6)

14.7 (0.7)

11.1 (0.4)

16.4 (0.5)

MRP(TNT)

29.4 (1.7)

18.4 (0.9)

14.1 (0.6)

11.2 (0.4)

17.7 (0.8)

MRL(RAxML)

15.9 (0.6)

14.0 (0.5)

12.9 (0.5)

11.2 (0.4)

13.4 (0.3)

SCM

6.3(0.5)

5.9(0.4)

4.7(0.3)

4.0(0.3)

5.2(0.2)

SuperFine+MRP(PAUP*)

13.9 (0.5)

12.6 (0.4)

11.5 (0.4)

11.1 (0.4)

12.2 (0.2)

SuperFine+MRP(TNT)

13.8 (0.6)

12.5 (0.4)

11.4 (0.4)

11.2 (0.4)

12.1 (0.2)

SuperFine+MRL(RAxML)

14.2 (0.5)

12.8 (0.4)

12.1 (0.4)

11.3 (0.4)

12.5 (0.2)

  1. We present the average false positive rates (reported as %) on the 500-taxon datasets. False positive rate is calculated as total number of FP edges in the estimated tree divided by the total number of internal edges in the internal tree. Each simulated dataset has 15 clade-based source trees and 1 scaffold tree. The scaffold density is the percentage of the full taxon set that is present in the scaffold tree. The standard error is shown in parenthesis. n = 24 for the 20% scaffold density, and n = 30 for the remaining scaffold densities. n = 114 for the average. The lowest false positive rate for each scaffold density is shown in bold.
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Algorithms for Molecular Biology

ISSN: 1748-7188