Felsenstein's Tree Peeling Algorithm
Encyclopedia
In statistical genetics, Felsenstein's tree-pruning algorithm (or Felsenstein's tree-peeling algorithm), due to Joseph Felsenstein
, is an algorithm
for computing the likelihood
of an evolutionary tree from nucleic acid
sequence data.
The algorithm is often used as a subroutine in a search for a maximum likelihood
estimate for an evolutionary tree. Further, it can be used in a hypothesis test for whether evolutionary rates are constant (by using likelihood ratio tests). It can also be used to provide error estimates for the parameters describing an evolutionary tree.
Joe Felsenstein
Joseph "Joe" Felsenstein is Professor in the Departments of Genome Sciences and Biology and Adjunct Professor in the Departments of Computer Science and Statistics at the University of Washington in Seattle...
, is an algorithm
Algorithm
In mathematics and computer science, an algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning...
for computing the likelihood
Likelihood
Likelihood is a measure of how likely an event is, and can be expressed in terms of, for example, probability or odds in favor.-Likelihood function:...
of an evolutionary tree from nucleic acid
Nucleic acid
Nucleic acids are biological molecules essential for life, and include DNA and RNA . Together with proteins, nucleic acids make up the most important macromolecules; each is found in abundance in all living things, where they function in encoding, transmitting and expressing genetic information...
sequence data.
The algorithm is often used as a subroutine in a search for a maximum likelihood
Maximum likelihood
In statistics, maximum-likelihood estimation is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum-likelihood estimation provides estimates for the model's parameters....
estimate for an evolutionary tree. Further, it can be used in a hypothesis test for whether evolutionary rates are constant (by using likelihood ratio tests). It can also be used to provide error estimates for the parameters describing an evolutionary tree.