Abstract
When multiple genes axe used in a phylogenetic study, the result is often a collection of incompatible trees. Phylogenetic networks and super-networks can be employed to analyze and visualize the incompatible signals in such a data set. In many situations, it is important to have control over the amount of imcompatibility that is represented in a phylogenetic network, for example reducing noise by removing splits that do not recur among the source trees. Current algorithms for computing hybridization networks from trees are based on a combinatorial analysis of the arising set of splits, and are thus sensitive to false positive splits. Here, a filter is desirable that can identify and remove splits that are not compatible with a hybridization scenario. To address these issues, the concept of the distortion of a tree relative to a split is defined as a measure of how much the tree needs to be modified in order to accommodate the split, and some of its properties are investigated. We demonstrate the usefulness of the approach by recovering a plausible hybridization scenario for buttercups from a pair of gene trees that cannot be obtained by existing methods. In a second example, a set of seven gene trees from microgastrine braconid wasps is investigated using filtered networks. A user-friendly implementation of the method is provided as a plug-in for the program SplitsTree4.
| Original language | English (US) |
|---|---|
| Title of host publication | Algorithms in Bioinformatics - 6th International Workshop, WABI 2006, Proceedings |
| Publisher | Springer-Verlag |
| Pages | 150-161 |
| Number of pages | 12 |
| ISBN (Print) | 3540395830, 9783540395836 |
| State | Published - Jan 1 2006 |
| Event | 6th International Workshop on Algorithms in Bioinformatics, WABI 2006 - Zurich, Switzerland Duration: Sep 11 2006 → Sep 13 2006 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4175 LNBI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 6th International Workshop on Algorithms in Bioinformatics, WABI 2006 |
|---|---|
| Country | Switzerland |
| City | Zurich |
| Period | 9/11/06 → 9/13/06 |
Fingerprint
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Reducing distortion in phylogenetic networks. / Huson, Daniel H.; Steel, Mike A.; Whitfield, James Bryan.
Algorithms in Bioinformatics - 6th International Workshop, WABI 2006, Proceedings. Springer-Verlag, 2006. p. 150-161 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4175 LNBI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Reducing distortion in phylogenetic networks
AU - Huson, Daniel H.
AU - Steel, Mike A.
AU - Whitfield, James Bryan
PY - 2006/1/1
Y1 - 2006/1/1
N2 - When multiple genes axe used in a phylogenetic study, the result is often a collection of incompatible trees. Phylogenetic networks and super-networks can be employed to analyze and visualize the incompatible signals in such a data set. In many situations, it is important to have control over the amount of imcompatibility that is represented in a phylogenetic network, for example reducing noise by removing splits that do not recur among the source trees. Current algorithms for computing hybridization networks from trees are based on a combinatorial analysis of the arising set of splits, and are thus sensitive to false positive splits. Here, a filter is desirable that can identify and remove splits that are not compatible with a hybridization scenario. To address these issues, the concept of the distortion of a tree relative to a split is defined as a measure of how much the tree needs to be modified in order to accommodate the split, and some of its properties are investigated. We demonstrate the usefulness of the approach by recovering a plausible hybridization scenario for buttercups from a pair of gene trees that cannot be obtained by existing methods. In a second example, a set of seven gene trees from microgastrine braconid wasps is investigated using filtered networks. A user-friendly implementation of the method is provided as a plug-in for the program SplitsTree4.
AB - When multiple genes axe used in a phylogenetic study, the result is often a collection of incompatible trees. Phylogenetic networks and super-networks can be employed to analyze and visualize the incompatible signals in such a data set. In many situations, it is important to have control over the amount of imcompatibility that is represented in a phylogenetic network, for example reducing noise by removing splits that do not recur among the source trees. Current algorithms for computing hybridization networks from trees are based on a combinatorial analysis of the arising set of splits, and are thus sensitive to false positive splits. Here, a filter is desirable that can identify and remove splits that are not compatible with a hybridization scenario. To address these issues, the concept of the distortion of a tree relative to a split is defined as a measure of how much the tree needs to be modified in order to accommodate the split, and some of its properties are investigated. We demonstrate the usefulness of the approach by recovering a plausible hybridization scenario for buttercups from a pair of gene trees that cannot be obtained by existing methods. In a second example, a set of seven gene trees from microgastrine braconid wasps is investigated using filtered networks. A user-friendly implementation of the method is provided as a plug-in for the program SplitsTree4.
UR - http://www.scopus.com/inward/record.url?scp=33750265162&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=33750265162&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33750265162
SN - 3540395830
SN - 9783540395836
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 150
EP - 161
BT - Algorithms in Bioinformatics - 6th International Workshop, WABI 2006, Proceedings
PB - Springer-Verlag
ER -