---+ Marker Divergence Experiments This workflow implements a method for extracting effective beneficial mutation rates (_μ_) and selection coefficients (_s_) from marker divergence experiments [[#ReferenceAnchor][[1]]]. This is a way of parameterizing the evolvability of a bacterial strain. %TOC% ---++ Requirements and Installation The Perl scripts require the module Math::Random::MT::Auto and its prerequisites for random number generation. They can be installed from [[http://www.cpan.org][CPAN]]. The Math::Random::MT::Auto module has a code component that must be compiled. If you have root access on a system you can probably install these from the command line as follows: <code><div style="border-color: grey; border-style: solid; border-width: 1px; padding:1px;"> >sudo perl -MCPAN -e shell<br> >Password: ********<br> >install Math::Random::MT::Auto<br> _answer yes to any prompts about installing prerequisites_ </div></code> ---++ 1. Fit α and τ Empirical Parameters from Experimental Data The basic command is: <code><div style="border-color: grey; border-style: solid; border-width: 1px; padding:1px;"> >sudo perl -MCPAN -e shell<br> >Password: ********<br> >install Math::Random::MT::Auto<br> _answer yes to any prompts about installing prerequisites_ </div></code> ---+++ Input File Data Format The input file is a tab-delimited. You should pass the =-m= option followed by =ratio=, =log_ratio=, =log10_ratio= to this script depending on the format of you data values. ---+++ Baseline Correction If some of your experimental curves do not start at a 1:1 ratio of the neutral marker states, you will also want to pass the =-b= option followed by the number of initial points (not transfers) . The script corrects for the initial marker imbalance by fitting τ and α to a modified equation that accounts for the fact that for a population diverging toward marker state _A_ where _A_ was initially present in less than 50% of the population, the marker ratio will be shifted sooner than in a population where it was initially present in 50% or more of the population. <code><div style="border-color: grey; border-style: solid; border-width: 1px; padding:1px;"> >sudo perl -MCPAN -e shell<br> >Password: ********<br> >install Math::Random::MT::Auto<br> _answer yes to any prompts about installing prerequisites_ </div></code> _Corrects for the baseline by taking the average of the first 5 points._ ---++ 2. Generate a Table of establishment probabilities with MATLAB. ---++ 3. Generate α and τ Values from a Population Genetics Simulation ---+++ 3.1 Generate Simulated Data for a _μ_ and _s_ Combination ---+++ 3.2 Fit α and τ Empirical Parameters from Experimental Data ---+++ 3.3 Helper Script: Automating this Step ---++ 4 Determine the Effective Parameters where Simulations and Experimental Data Produce the Same Distributions of Empirical Parameters ---++ References #ReferenceAnchor 1 Hegreness, M., Shoresh, N., Hartl, D., and Kishony, R. (2006) An equivalence principle for the incorporation of favorable mutations in asexual populations. Science 311, 1615-1617. 1 Wahl, L.M., and Gerrish, P.J. (2001) The probability that beneficial mutations are lost in populations with periodic bottlenecks. Evolution 55, 2606-2610. ---++ Acknowledgments Many thanks to Noam Shoresh for extensive discussions that made it possible for me to reproduce his methods and providing his raw data to check the results from these tools.
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Topic revision: r2 - 2008-09-19 - JeffreyBarrick