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## Overview of LAMARC

LAMARC is a large, complex, powerful set of data analysis tools to do coalescence of populations. It can calculate a wide variety of forces and use a large number of different methods. Because of all its options it is not easy to learn. We have done our best to cover the topics that most people need in this web site, but you need to both read the documents and be willing to experiment with various methods to find what works for your data. We recommend that you read about LAMARC's strengths and limits before you start collecting data. We also realize this is unlikely to happen. We will be glad to help as much as we can, both with experimental design and how to do data analysis, but, ultimately, you are the expert on your data and know what you need. We can only help you with how you ask your questions.

## Family tree

All versions of LAMARC combine much of the capabilities of the previous programs MIGRATE, RECOMBINE, and FLUCTUATE, and each has added new functionality as well. Using DNA or RNA sequence data, SNPs, microsatellites, or K-Allele data such as electrophoretic alleles, LAMARC can estimate Theta, recombination rate, migration rates, and growth (or decline) rates for the population(s) from which the data were drawn. These four forces can be estimated all together or with any sub-combination that includes Theta (i.e. Theta plus up to three other forces). It can also make estimates using genotyped (or unphased) data.

As of version 2.1, LAMARC can now be used for fine-scale mapping of trait data. Recombination is required for this capability, which can be performed in the presence or absence of migration or growth.

The older programs RECOMBINE and FLUCTUATE are no longer being actively supported, as their capabilities have been incorporated into LAMARC. MIGRATE is now being maintained by Peter Beerli at Florida State University. He has taken the program in a slightly different direction than LAMARC, and it now offers unique features such as the ability to run the program in parallel on a cluster, and various diverse models for migration.

The primary advantage of LAMARC over the older programs is its ability to simultaneously estimate what the other programs estimated separately. Even if you are primarily interested in only one of these, their simultaneous estimation means that your estimates will not be biased by the unacknowledged presence of the other.

LAMARC is written in C++. Each release includes executables which should run on current versions of Linux, OS X, and MS Windows. For more information see Compiling Lamarc.

The program is free to download and use. We would appreciate hearing about any publications resulting from it. To cite LAMARC, you can reference our announcement paper:

Kuhner, M. K., 2006 "LAMARC 2.0: maximum likelihood and Bayesian estimation of population parameters." Bioinformatics 22(6): 768-770.

For more information about the Bayesian aspects of the program, see:

Kuhner, M. K. and L. P. Smith, 2007 "Comparing Likelihood and Bayesian Coalescent Estimation of Population Parameters" Genetics 175: 155-165.

Bug reports, comments, critiques, and notices of papers can be sent to lamarc@u.washington.edu.

The program can be found for download on our Web site:

http://evolution.gs.washington.edu/lamarc/

#### About the Authors:

The LAMARC program is currently being developed at the University of Washington in the Felsenstein/Kuhner lab. The list of contributors includes:

- Mary K. Kuhner (UW, current development team)
- Jon Yamato (UW, current)
- Bob Giansiracusa (UW, current)
- Jim McGill (UW, current)
- Elizabeth Walkup (UW, current)
- Peter Beerli (FSU, former contributor, now working on MIGRATE)
- Patrick Colacurcio (UW, former contributor)
- Chia-Chi Li (UW, former)
- Eric Rynes (UW, former)
- Jim Sloan (UW, former)
- Lucian Smith (UW, former)
- Wang Yi (UW, former)

Other people and organizations who have provided essential infrastructure support for this project:

- Boost for providing the smart_ptr implementation
- GNU for the g++ compiler, gdb debugger, and CVS source control system used to develop this program.
- Lee Thomason and Yves Berquin for their TinyXML parser.
- wxWidgets for the tools to make the new GUI for our file converter.
- Matthew Austern in particular and the denizens of the usenet newsgroup comp.lang.c++.moderated in general for helpful advice.

Funding for this project was provided by the National Institutes of Health grants GM 51929-02 and HG 01989-02, both to Joseph Felsenstein, and the NIH grant GM 51929-10 to Mary K. Kuhner.

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