NDLI: Incomplete taxon sampling is not a problem for phylogenetic inference

Content Provider	PubMed Central
Author	Rosenberg, Michael S. Kumar, Sudhir
Copyright Year	2001
Abstract	A major issue in all data collection for molecular phylogenetics is taxon sampling, which refers to the use of data from only a small representative set of species for inferring higher-level evolutionary history. Insufficient taxon sampling is often cited as a significant source of error in phylogenetic studies, and consequently, acquisition of large data sets is advocated. To test this assertion, we have conducted computer simulation studies by using natural collections of evolutionary parameters—rates of evolution, species sampling, and gene lengths—determined from data available in genomic databases. A comparison of the true tree with trees constructed by using taxa subsamples and trees constructed by using all taxa shows that the amount of phylogenetic error per internal branch is similar; a result that holds true for the neighbor-joining, minimum evolution, maximum parsimony, and maximum likelihood methods. Furthermore, our results show that even though trees inferred by using progressively larger taxa subsamples of a real data set become increasingly similar to trees inferred by using the full sample, all inferred trees are equidistant from the true tree in terms of phylogenetic error per internal branch. Our results suggest that longer sequences, rather than extensive sampling, will better improve the accuracy of phylogenetic inference.
Related Links	http://dx.doi.org/10.1073/pnas.191248498
Ending Page	10756
Page Count	6
Starting Page	10751
File Format	PDF
ISSN	00278424
e-ISSN	10916490
Journal	Proceedings of the National Academy of Sciences of the United States of America
Issue Number	19
Volume Number	98
Language	English
Publisher	The National Academy of Sciences
Publisher Date	2001-09-11
Access Restriction	Open
Rights Holder	The National Academy of Sciences
Subject Keyword	General Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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