CVTree: a phylogenetic tree reconstruction tool based on whole genomes

Qi, Ji; Luo, Hong; Hao, Bailin

doi:10.1093/nar/gkh362

Cited by 190 publications

(155 citation statements)

References 21 publications

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“…A similar alignmentfree proteome tree for the fungal proteome sequence, constructed using a different alignment-free method (composition vector or CV) (31,32), reported that the CV tree supported largely the MSA-based gene trees. This conclusion is different from ours for several reasons.…”

Section: Other Notable Differences Between the Features Of The Proteomementioning

confidence: 97%

A genome Tree of Life for the Fungi kingdom

Choi

Kim

2017

Proc. Natl. Acad. Sci. U.S.A.

126

108

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Fungi belong to one of the largest and most diverse kingdoms of living organisms. The evolutionary kinship within a fungal population has so far been inferred mostly from the gene-information–based trees (“gene trees”), constructed commonly based on the degree of differences of proteins or DNA sequences of a small number of highly conserved genes common among the population by a multiple sequence alignment (MSA) method. Since each gene evolves under different evolutionary pressure and time scale, it has been known that one gene tree for a population may differ from other gene trees for the same population depending on the subjective selection of the genes. Within the last decade, a large number of whole-genome sequences of fungi have become publicly available, which represent, at present, the most fundamental and complete information about each fungal organism. This presents an opportunity to infer kinship among fungi using a whole-genome information-based tree (“genome tree”). The method we used allows comparison of whole-genome information without MSA, and is a variation of a computational algorithm developed to find semantic similarities or plagiarism in two books, where we represent whole-genomic information of an organism as a book of words without spaces. The genome tree reveals several significant and notable differences from the gene trees, and these differences invoke new discussions about alternative narratives for the evolution of some of the currently accepted fungal groups.

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Section: Other Notable Differences Between the Features Of The Proteomementioning

confidence: 97%

A genome Tree of Life for the Fungi kingdom

Choi

Kim

2017

Proc. Natl. Acad. Sci. U.S.A.

126

108

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“…We have built a public web server named CVTree [11] . Throughout this paper we use CVTree both as a shorthand for the method and for the tree thus obtained.…”

mentioning

confidence: 99%

Prokaryote phylogeny meets taxonomy: An exhaustive comparison of composition vector trees with systematic bacteriology

Gao

Sun

et al. 2007

SCI CHINA SER C

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We perform an exhaustive, taxon by taxon, comparison of the branchings in the composition vector trees (CVTrees) inferred from 432 prokaryotic genomes available on 31 December 2006, with the bacteriologists' taxonomy--primarily the latest online Outline of the Bergey's Manual of Systematic Bacteriology. The CVTree phylogeny agrees very well with the Bergey's taxonomy in majority of fine branchings and overall structures. At the same time most of the differences between the trees and the Manual have been known to biologists to some extent and may hint at taxonomic revisions. Instead of demonstrating the overwhelming agreement this paper puts emphasis on the biological implications of the differences.

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“…The Composition Vector (CV) method has become a popular approach for phylogenetic tree generation which is evident due to the many different approaches proposed for this method ( [11]- [14]). Since we target an optimization for one of the common basic step in CV method, many of the applications written for different CV method based approaches will benefit from it.…”

Section: Related Workmentioning

confidence: 99%

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

Krishnajith

Kelly

Hayward

et al. 2013

2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)

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Abstract-The generation of a correlation matrix from a large set of long gene sequences is a common requirement in many bioinformatics problems such as phylogenetic analysis. The generation is not only computationally intensive but also requires significant memory resources as, typically, few gene sequences can be simultaneously stored in primary memory. The standard practice in such computation is to use frequent input/output (I/O) operations. Therefore, minimizing the number of these operations will yield much faster run-times. This paper develops an approach for the faster and scalable computing of large-size correlation matrices through the full use of available memory and a reduced number of I/O operations. The approach is scalable in the sense that the same algorithms can be executed on different computing platforms with different amounts of memory and can be applied to different problems with different correlation matrix sizes. The significant performance improvement of the approach over the existing approaches is demonstrated through benchmark examples.

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CVTree: a phylogenetic tree reconstruction tool based on whole genomes

Cited by 190 publications

References 21 publications

A genome Tree of Life for the Fungi kingdom

A genome Tree of Life for the Fungi kingdom

Prokaryote phylogeny meets taxonomy: An exhaustive comparison of composition vector trees with systematic bacteriology

Managing memory and reducing I/O cost for correlation matrix calculation in bioinformatics

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