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LineageSpecificSeqgen: generating sequence data with lineage-specific variation in the proportion of variable sites
Citation
Grievink, LS and Penny, D and Hendy, MD and Holland, BR, LineageSpecificSeqgen: generating sequence data with lineage-specific variation in the proportion of variable sites, BMC Evolutionary Biology, 8, (1) pp. 1-6. ISSN 1471-2148 (2008) [Refereed Article]
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Copyright Statement
© 2008 Grievink et al
DOI: doi:10.1186/1471-2148-8-317
Abstract
Background: Commonly used phylogenetic models assume a homogeneous evolutionary process
throughout the tree. It is known that these homogeneous models are often too simplistic, and that
with time some properties of the evolutionary process can change (due to selection or drift). In
particular, as constraints on sequences evolve, the proportion of variable sites can vary between
lineages. This affects the ability of phylogenetic methods to correctly estimate phylogenetic trees,
especially for long timescales. To date there is no phylogenetic model that allows for change in the
proportion of variable sites, and the degree to which this affects phylogenetic reconstruction is
unknown.
Results: We present LineageSpecificSeqgen, an extension to the seq-gen program that allows
generation of sequences with both changes in the proportion of variable sites and changes in the
rate at which sites switch between being variable and invariable. In contrast to seq-gen and its
derivatives to date, we interpret branch lengths as the mean number of substitutions per variable
site, as opposed to the mean number of substitutions per site (which is averaged over all sites,
including invariable sites). This allows specification of the substitution rates of variable sites,
independently of the proportion of invariable sites.
Conclusion: LineageSpecificSeqgen allows simulation of DNA and amino acid sequence alignments
under a lineage-specific evolutionary process. The program can be used to test current models of
evolution on sequences that have undergone lineage-specific evolution. It facilitates the
development of both new methods to identify such processes in real data, and means to account
for such processes. The program is available at: http://awcmee.massey.ac.nz/downloads.htm.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Research Division: | Information and Computing Sciences |
| Research Group: | Applied computing |
| Research Field: | Applications in life sciences |
| Objective Division: | Expanding Knowledge |
| Objective Group: | Expanding knowledge |
| Objective Field: | Expanding knowledge in the biological sciences |
| UTAS Author: | Holland, BR (Professor Barbara Holland) |
| ID Code: | 63088 |
| Year Published: | 2008 |
| Web of Science® Times Cited: | 10 |
| Deposited By: | Mathematics |
| Deposited On: | 2010-04-14 |
| Last Modified: | 2012-04-02 |
| Downloads: | 362 View Download Statistics |
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