Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > q-bio > arXiv:1307.1586

Help | Advanced Search

Quantitative Biology > Populations and Evolution

arXiv:1307.1586 (q-bio)
[Submitted on 5 Jul 2013 ]

Title: Evaluating strategies of phylogenetic analyses by the coherence of their results

Title: 通过结果的一致性评估系统发育分析的策略

Authors:Blaise Li
Abstract: I propose an approach to identify, among several strategies of phylogenetic analysis, those producing the most accurate results. This approach is based on the hypothesis that the more a result is reproduced from independent data, the more it reflects the historical signal common to the analysed data. Under this hypothesis, the capacity of an analytical strategy to extract historical signal should correlate positively with the coherence of the obtained results. I apply this approach to a series of analyses on empirical data, basing the coherence measure on the Robinson-Foulds distances between the obtained trees. At first approximation, the analytical strategies most suitable for the data produce the most coherent results. However, risks of false positives and false negatives are identified, which are difficult to rule out.
Abstract: 我提出一种方法,在多种系统发育分析策略中,识别出产生最准确结果的策略。 该方法基于这样一个假设:一个结果从独立数据中重复的次数越多,它就越能反映分析数据中共有的历史信号。 在这一假设下,分析策略提取历史信号的能力应与获得结果的一致性呈正相关。 我将这种方法应用于对实证数据的一系列分析,将一致性度量基于获得的树之间的Robinson-Foulds距离。 初步来看,最适合数据的分析策略会产生最一致的结果。 然而,发现了假阳性与假阴性的风险,这些风险难以排除。
Comments: 6 pages, 3 figures, accepted for publication in Comptes Rendus Palevol, based on a work presented at the "Journ\'ees d'automne 2012 de la Soci\'et\'e Fran\c{c}aise de Syst\'ematique" (http://www.normalesup.org/~bli/Papers/SFS_2012_BL.pdf)
Subjects: Populations and Evolution (q-bio.PE)
Cite as: arXiv:1307.1586 [q-bio.PE]
  (or arXiv:1307.1586v1 [q-bio.PE] for this version)
  https://doi.org/10.48550/arXiv.1307.1586
arXiv-issued DOI via DataCite

Submission history

From: Blaise Li [view email]
[v1] Fri, 5 Jul 2013 11:36:40 UTC (32 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
q-bio.PE
< prev   |   next >
new | recent | 2013-07
Change to browse by:
q-bio

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号