| 1. |
- Huber, Katharina T., et al.
(författare)
-
Reconstructing the evolutionary history of polyploids from multilabeled trees
- 2006
-
Ingår i: Molecular biology and evolution. - : Oxford University Press (OUP). - 0737-4038 .- 1537-1719. ; 23:9, s. 1784-1791
-
Tidskriftsartikel (refereegranskat)abstract
- In recent studies, phylogenetic networks have been derived from so-called multilabeled trees in order to understand the origins of certain polyploids. Although the trees used in these studies were constructed using sophisticated techniques in phylogenetic analysis, the presented networks were inferred using ad hoc arguments that cannot be easily extended to larger, more complicated examples. In this paper, we present a general method for constructing such networks, which takes as input a multilabeled phylogenetic tree and outputs a phylogenetic network with certain desirable properties. To illustrate the applicability of our method, we discuss its use in reconstructing the evolutionary history of plant allopolyploids. We conclude with a discussion concerning possible future directions. The network construction method has been implemented and is freely available for use from http://www.uea.ac.uk/similar to a043878/padre.html.
|
|
| 2. |
- Strimmer, K., et al.
(författare)
-
Likelihood analysis of phylogenetic networks using directed graphical models
- 2000
-
Ingår i: Molecular biology and evolution. - 0737-4038 .- 1537-1719. ; 17:6, s. 875-881
-
Tidskriftsartikel (refereegranskat)abstract
- A method for computing the likelihood of a set of sequences assuming a phylogenetic network as an evolutionary hypothesis is presented. The approach applies directed graphical models to sequence evolution on networks and is a natural generalization of earlier work by Felsenstein on evolutionary trees, including it as a special case. The likelihood computation involves several steps. First, the phylogenetic network is rooted to form a directed acyclic graph (DAG). Then, applying standard models for nucleotide/amino acid substitution, the DAG is converted into a Bayesian network from which the joint probability distribution involving all nodes of the network can be directly read. The joint probability is explicitly dependent on branch lengths and on recombination parameters (prior probability of a parent sequence). The likelihood of the data assuming no knowledge of hidden nodes is obtained by marginalization, i.e., by summing over all combinations of unknown states. As the number of terms increases exponentially with the number of hidden nodes, a Markov chain Monte Carlo procedure (Gibbs sampling) is used to accurately approximate the likelihood by summing over the most important states only. Investigating a human T-cell lymphotropic virus (HTLV) data set and optimizing both branch lengths and recombination parameters, we find that the likelihood of a corresponding phylogenetic network outperforms a set of competing evolutionary trees. In general, except for the case of a tree, the likelihood of a network will be dependent on the choice of the root, even if a reversible model of substitution is applied. Thus, the method also provides a way in which to root a phylogenetic network by choosing a node that produces a most likely network.
|
|
| 3. |
|
|
| 4. |
- Grünewald, Stefan, et al.
(författare)
-
QNet : an agglomerative method for the construction of phylogenetic networks from weighted quartets.
- 2007
-
Ingår i: Mol Biol Evol. - 0737-4038. ; 24:2, s. 532-8
-
Tidskriftsartikel (refereegranskat)abstract
- We present QNet, a method for constructing split networks from weighted quartet trees. QNet can be viewed as a quartet analogue of the distance-based Neighbor-Net (NNet) method for network construction. Just as NNet, QNet works by agglomeratively computing a collection of circular weighted splits of the taxa set which is subsequently represented by a planar split network. To illustrate the applicability of QNet, we apply it to a previously published Salmonella data set. We conclude that QNet can provide a useful alternative to NNet if distance data are not available or a character-based approach is preferred. Moreover, it can be used as an aid for determining when a quartet-based tree-building method may or may not be appropriate for a given data set. QNet is freely available for download.
|
|
| 5. |
|
|
