Abstract
Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.
Original language | English (US) |
---|---|
Pages (from-to) | 101-109 |
Number of pages | 9 |
Journal | Molecular Biology and Evolution |
Volume | 19 |
Issue number | 1 |
State | Published - 2002 |
Externally published | Yes |
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Keywords
- Evolutionary rates
- Molecular clock
- Penalized likelihood
ASJC Scopus subject areas
- Genetics
- Biochemistry
- Genetics(clinical)
- Biochemistry, Genetics and Molecular Biology(all)
- Ecology, Evolution, Behavior and Systematics
- Agricultural and Biological Sciences (miscellaneous)
- Molecular Biology
Cite this
Estimating absolute rates of molecular evolution and divergence times : A penalized likelihood approach. / Sanderson, Michael.
In: Molecular Biology and Evolution, Vol. 19, No. 1, 2002, p. 101-109.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Estimating absolute rates of molecular evolution and divergence times
T2 - A penalized likelihood approach
AU - Sanderson, Michael
PY - 2002
Y1 - 2002
N2 - Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.
AB - Rates of molecular evolution vary widely between lineages, but quantification of how rates change has proven difficult. Recently proposed estimation procedures have mainly adopted highly parametric approaches that model rate evolution explicitly. In this study, a semiparametric smoothing method is developed using penalized likelihood. A saturated model in which every lineage has a separate rate is combined with a roughness penalty that discourages rates from varying too much across a phylogeny. A data-driven cross-validation criterion is then used to determine an optimal level of smoothing. This criterion is based on an estimate of the average prediction error associated with pruning lineages from the tree. The methods are applied to three data sets of six genes across a sample of land plants. Optimally smoothed estimates of absolute rates entailed 2- to 10-fold variation across lineages.
KW - Evolutionary rates
KW - Molecular clock
KW - Penalized likelihood
UR - http://www.scopus.com/inward/record.url?scp=0036135468&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0036135468&partnerID=8YFLogxK
M3 - Article
C2 - 11752195
AN - SCOPUS:0036135468
VL - 19
SP - 101
EP - 109
JO - Molecular Biology and Evolution
JF - Molecular Biology and Evolution
SN - 0737-4038
IS - 1
ER -