Phylogenetic analysis of Polyomaviruses Based on Their Complete Genomes

A method based on the improved inter-nucleotide distances of genomes to construct vertebrates phylogeny tree

“…With genomic data available, the sequence alignment methods for so large quantities of data now become unrealistic, because the complexities of space and time have not reached a satisfactory level. So, some new phylogenetic tree construction methods have been proposed without sequence alignment, such as, information theory [8,9], principal component analysis [10], singular value decomposition (SVD) method [11,12], Markov model [13,14], dynamic language method [15][16][17][18] and so on.…”

The methods of log-correlation distance and mutual information for constructing genome phylogenetic tree of parvoviruses

“…But given that most genomes contain millions to billions of sequence characters, standard methods based on character-by-character comparisons performed over ambiguously resolved large-scale alignments become impractical [11]. Hence, so far many alignment-free methods to construct the phylogenetic tree have been proposed, for example, information-based methods [12][13][14], principal component analysis [15], singular value decomposition (SVD) [11,16,17], fractal analysis [18][19][20], Markov model [1,21,22], dynamical language model [23,24], log-correlation distance and Fourier transform with Kullback-Leibler divergence distance [25]. In our previous work, log-correlation distance method [25] and mutual information method [14] were used to construct 64 vertebrate phylogenetic tree based on complete mitochondrial genomes and the tree was separated into three major group (mammals, fish and archosauria) and was roughly in agreement in topology with the known phylogenies of vertebrates.…”

Proper Distance Metrics for Phylogenetic Analysis Using Complete Genomes without Sequence Alignment

“…A number of methods without sequence alignment for deriving species phylogeny based on overall similarities of complete genomes have been developed. These include fractal analysis [ 2 – 4 ], dynamical language model [ 5 ], information-based analysis [ 6 – 8 ], log-correlation distance and Fourier transformation with Kullback-Leibler divergence distance [ 9 ], Markov model [ 10 – 15 ], principal component analysis [ 16 ] and singular value decomposition (SVD) [ 17 – 19 ]. The analyses based on the Markov model and dynamical language model without sequence alignment using 103 prokaryotes and 6 eukaryotes have yielded trees separating the three domains of life, Archaea, Eubacteria and Eukarya, with the relationships among the taxa consistent with those based on traditional analyses [ 5 , 11 ].…”