Difference: ToolsMarkerDivergence (1 vs. 2)

Revision 22008-09-19 - JeffreyBarrick

  META TOPICPARENT 
 name="ToolList" 

 Marker Divergence Experiments
- META TOPICPARENT
+ name="ToolList"
-<
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+This workflow implements a method for extracting effective beneficial mutation rates (μ) and selection coefficients (s)from marker divergence experiments [1]. This is a way of parameterizing the evolvability of a bacterial strain.
->
>
+This workflow implements a method for extracting effective beneficial mutation rates (μ) and selection coefficients (s) from marker divergence experiments [1]. This is a way of parameterizing the evolvability of a bacterial strain.
   Marker Divergence Experiments 
  Example Data
   Requirements and Installation
   1. Fit α and τ empirical parameters from experimental data 
  Input file data format
   Baseline correction
 
   2. Generate a table of establishment probabilities with MATLAB.
   3. Simulate and fit idealized marker divergence curves 
  3.1 Simulate marker divergence data for a set of μ and s effective beneficial mutation parameters
   3.2 Fit α and τ empirical parameters from simulated curves
   3.3 Automating and parallelizing this step
 
   4. Determine the maximum likelihood effective parameters
   References
   Acknowledgments
 
 


 Requirements and Installation
-<
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+The Perl scripts require the module Math::Random::MT::Auto and its prerequisites. They can be installed from CPAN. The Math::Random::MT::Auto module has a code component that must be compiled. On many systems you can install these from the command line as follows:
->
>
+The Perl scripts require the module Math::Random::MT::Auto and its prerequisites for random number generation. They can be installed from 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:
  >sudo perl -MCPAN -e shell

 >Password: ********

 >install Math::Random::MT::Auto
-<
<
+answer yes to any prompts about installing prerequisites
->
>
+  _answer yes to any prompts about installing prerequisites_
 . Fit α and τ Empirical Parameters from Experimental Data
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>
+The basic command is:

 >sudo perl -MCPAN -e shell

 >Password: ********

 >install Math::Random::MT::Auto

  _answer yes to any prompts about installing prerequisites_


 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.


 >sudo perl -MCPAN -e shell

 >Password: ********

 >install Math::Random::MT::Auto

  _answer yes to any prompts about installing prerequisites_


Corrects for the baseline by taking the average of the first 5 points.
 . 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 
 
 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.
  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.

Revision 12008-09-18 - JeffreyBarrick

META TOPICPARENT	name="ToolList"

Marker Divergence Experiments

This workflow implements a method for extracting effective beneficial mutation rates (μ) and selection coefficients (s)from marker divergence experiments [1]. This is a way of parameterizing the evolvability of a bacterial strain.

Marker Divergence Experiments

Requirements and Installation

The Perl scripts require the module Math::Random::MT::Auto and its prerequisites. They can be installed from CPAN. The Math::Random::MT::Auto module has a code component that must be compiled. On many systems you can install these from the command line as follows:


 >sudo perl -MCPAN -e shell

 >Password: ********

 >install Math::Random::MT::Auto

answer yes to any prompts about installing prerequisites

1. Fit α and τ Empirical Parameters from Experimental Data

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

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.
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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