# Difference between revisions of "R Hackathon 1/Trait Evolution SG"

From Phyloinformatics

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#** geiger and mesquite are consistent, returning the same parameter estimates and likelihoods | #** geiger and mesquite are consistent, returning the same parameter estimates and likelihoods | ||

#** geiger and ape are different | #** geiger and ape are different | ||

− | #** ape is reporting the joint likelihoods for ancestral states. This | + | #** ape is reporting the joint likelihoods for ancestral states. This uses the single set of ancestral states that together result in the highest likelihood on the whole tree. |

− | states that together result in the highest likelihood on the whole tree. mesquite and geiger use | + | #** mesquite and geiger use marginal likelihoods for ancestral states. This represents the likelihood averaged over all possible ancestral character state values. |

− | marginal likelihoods for ancestral states. This represents the likelihood averaged over all possible ancestral character state values. | ||

# Improve functionality or, at least, interpretability of output | # Improve functionality or, at least, interpretability of output | ||

#* GEIGER was modified to give more reliable results by a more thorough search of the likelihood surface | #* GEIGER was modified to give more reliable results by a more thorough search of the likelihood surface |

## Revision as of 16:31, 24 January 2008

- Participants: Harmon, Hipp, Hunt

## Targets.

- Compare various implementations of the same methods (ape, geiger, OUCH, Mesquite)
- Improve functionality of character fitting in r
- Investigate statistical power of discriminating among various models
- Identify gaps in current implementation

## Accomplishments.

- Evaluated the results of continuous character analyses in different packages
- Packages are mostly consistent
- Discrepancies come from two sources:
- Different approaches (e.g. marginal versus joint likelihood)
- Difficulties in finding the ML solution

- For continuous characters:
- geiger and OUCH tend to return the same parameter estimates
- But they return different likelihoods

- For discrete characters
- geiger and mesquite are consistent, returning the same parameter estimates and likelihoods
- geiger and ape are different
- ape is reporting the joint likelihoods for ancestral states. This uses the single set of ancestral states that together result in the highest likelihood on the whole tree.
- mesquite and geiger use marginal likelihoods for ancestral states. This represents the likelihood averaged over all possible ancestral character state values.

- Improve functionality or, at least, interpretability of output
- GEIGER was modified to give more reliable results by a more thorough search of the likelihood surface
- Some ape functions seem (to us) unreliable for large trees

Test

- Clarified why one sometimes gets different results from different programs
- Modified GEIGER package so that results for fitting models of character evolution are more robust
- Modified functions to rescale trees and variance-covariance matrices for non-ultrametric trees