Machine learning based imputation techniques for estimating phylogenetic trees from incomplete distance matrices

BMC Genomics

Table 2 Average RF rates (± standard error) of different methods on the 37-taxon dataset for varying numbers of missing entries and two different sequence evolution models. For each model condition, we show the average RF rate and standard error over 10 replicates. The best RF rates for various model conditions are shown in boldface

#Taxa	#Entries	Scaling	Model	#Missing	Average RF Rate
				Entries	DAMBE	LASSO	MF	AE
				36	0.41 ±0.02	0.72 ±0.03	0.33 ±0.03	0.41 ±0.02
				100	0.48 ±0.02	0.72 ±0.03	0.46 ±0.02	0.45 ±0.02
			TN93	225	0.72 ±0.03	0.78 ±0.03	0.62 ±0.01	0.70 ±0.02
37	666	1X		342	N/A	N/A	0.99 ±0.02	0.86 ±0.01
				36	0.41 ±0.02	0.71 ±0.02	0.35 ±0.03	0.4 ±0.02
				100	0.49 ±0.02	0.72 ±0.02	0.5 ±0.03	0.46 ±0.02
			LogDet	225	0.72 ±0.02	0.76 ±0.02	0.66 ±0.03	0.72 ±0.02
				342	N/A	N/A	1 ±0	0.86 ±0.02
				36	0.45 ±0.02	0.69 ±0.02	0.35 ±0.02	0.43 ±0.02
				100	0.49 ±0.03	0.72 ±0.02	0.5 ±0.02	0.54 ±0.03
			TN93	225	0.66 ±0.02	0.76 ±0.02	0.62 ±0.01	0.71 ±0.02
37	666	0.5X		342	N/A	N/A	1 ±0	0.84 ±0.02
				36	0.45 ±0.02	0.68 ±0.02	0.35 ±0.02	0.42 ±0.02
				100	0.49 ±0.03	0.71 ±0.02	0.52 ±0.02	0.51 ±0.02
			LogDet	225	0.64 ±0.02	0.76 ±0.01	0.66 ±0.02	0.7 ±0.02
				342	N/A	N/A	0.99 ±0.02	0.84 ±0.02
				36	0.43 ±0.02	0.68 ±0.01	0.36 ±0.03	0.42 ±0.02
				100	0.5 ±0.01	0.69 ±0.02	0.52 ±0.02	0.5 ±0.02
			TN93	225	0.66 ±0.02	0.73 ±0.02	0.71 ±0.02	0.69 ±0.02
37	666	2X		342	N/A	N/A	0.99 ±0.01	0.85 ±0.01
				36	0.44 ±0.02	0.63 ±0.02	0.36 ±0.02	0.4 ±0.01
				100	0.51 ±0.02	0.66 ±0.02	0.54 ±0.02	0.52 ±0.02
			LogDet	225	0.66 ±0.02	0.73 ±0.01	0.7 ±0.02	0.69 ±0.02
				342	N/A	N/A	0.99 ±0.01	0.86 ±0.02

ISSN: 1471-2164