Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If you need an accessible version of this item please contact JSTOR User Support

Combining Trees as a Way of Combining Data Sets for Phylogenetic Inference, and the Desirability of Combining Gene Trees

Bernard R. Baum
Taxon
Vol. 41, No. 1 (Feb., 1992), pp. 3-10
DOI: 10.2307/1222480
Stable URL: http://www.jstor.org/stable/1222480
Page Count: 8
  • Read Online (Free)
  • Download ($14.00)
  • Cite this Item
If you need an accessible version of this item please contact JSTOR User Support
Combining Trees as a Way of Combining Data Sets for Phylogenetic Inference, and the Desirability of Combining Gene Trees
Preview not available

Abstract

A procedure of combining trees obtained from data sets of different kinds, similar to Brooks's technique but for a different purpose, with the aim of combining these data sets, is detailed along with examples used in five unrepeated combinations from a total of 15 published datasets. The procedure does not adjoin raw data sets, but instead combines the binary-coded factors of the trees, each tree from a different data set, together. This allows the combining of data that are only available as pair-wise distances with data obtained directly from characters of the organisms. It economizes the analysis of combined nucleotide sequence data which can be very large, and preserves information for each kind of data in the combination. The procedure allows for missing data as well, and can be regarded as a new consensus method -- mathematical properties have yet to be investigated. The desirability of combining gene trees, obtained from molecular data, to enable the inference of species trees is discussed in light of using this procedure.

Page Thumbnails

  • Thumbnail: Page 
3
    3
  • Thumbnail: Page 
4
    4
  • Thumbnail: Page 
5
    5
  • Thumbnail: Page 
6
    6
  • Thumbnail: Page 
7
    7
  • Thumbnail: Page 
8
    8
  • Thumbnail: Page 
9
    9
  • Thumbnail: Page 
10
    10