Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification...Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification of the inferred phylogeny. In this work, we show the stability and self-consistency of CVTrees by performing bootstrap and jackknife re-sampling tests adapted to this alignment-free approach. Our ultimate goal is to advocate the viewpoint that time-consuming statistical re-sampling tests can be avoided at all in using this alignment-free approach. Agreement with taxonomy should be taken as a major criterion to estimate prokaryotic phylogenetic trees.展开更多
基金supported by the National Basic Research Program of China (the 973 Program, Grant No. 2007CB814800)the Shanghai Leading Academic Discipline Project (Grant No. B111)
文摘Composition vector trees （CVTrees） are inferred from whole-genome data by an alignment-free and parameter-free method. The agreement of these trees with the corresponding taxonomy provides an objective justification of the inferred phylogeny. In this work, we show the stability and self-consistency of CVTrees by performing bootstrap and jackknife re-sampling tests adapted to this alignment-free approach. Our ultimate goal is to advocate the viewpoint that time-consuming statistical re-sampling tests can be avoided at all in using this alignment-free approach. Agreement with taxonomy should be taken as a major criterion to estimate prokaryotic phylogenetic trees.
