4.8 Article

A novel methodology for large-scale phylogeny partition

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NATURE COMMUNICATIONS
卷 2, 期 -, 页码 -

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NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms1325

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资金

  1. European Commission [233847]
  2. European Community [223131]
  3. NIH-NINDS [R01 NS063897-01A2]
  4. Abbott
  5. Boehringer-Ingelheim
  6. Bristol-Myers Squibb
  7. Gilead Sciences
  8. GlaxoSmithKline
  9. Janssen-Cilag Tibotec division
  10. T-32 National Cancer Institute [T-32 CA09126]

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Understanding the determinants of virus transmission is a fundamental step for effective design of screening and intervention strategies to control viral epidemics. Phylogenetic analysis can be a valid approach for the identification of transmission chains, and very-large data sets can be analysed through parallel computation. Here we propose and validate a new methodology for the partition of large-scale phylogenies and the inference of transmission clusters. This approach, on the basis of a depth-first search algorithm, conjugates the evaluation of node reliability, tree topology and patristic distance analysis. The method has been applied to identify transmission clusters of a phylogeny of 11,541 human immunodeficiency virus-1 subtype B pol gene sequences from a large Italian cohort. Molecular transmission chains were characterized by means of different clinical/demographic factors, such as the interaction between male homosexuals and male heterosexuals. Our method takes an advantage of a flexible notion of transmission cluster and can become a general framework to analyse other epidemics.

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