User:Hussein Alasadi/Notebook/stephens/2013/10/16: Difference between revisions

From OpenWetWare
Jump to navigationJump to search
Line 12: Line 12:


* '''We then evolve the populations for g generations with recombination'''
* '''We then evolve the populations for g generations with recombination'''
To do this we can use Kessner's [http://arxiv.org/abs/1310.3234 Forqs]. Forqs allows the user to specify the recombination rate file which might be useful in the future.
To do this we can use Kessner's [http://arxiv.org/abs/1310.3234 Forqs]. Forqs allows the user to specify the recombination rate file which might be useful in the future. Also Forqs was written in way with selection experiments in mind, they have functions such as "Quantitative Trait" that allows the user to define the fitness function in a complex way.


* '''Simulate pooled sequencing'''
* '''Simulate pooled sequencing'''

Revision as of 08:58, 17 October 2013

Analyzing pooled sequenced data with selection <html><img src="/images/9/94/Report.png" border="0" /></html> Main project page
<html><img src="/images/c/c3/Resultset_previous.png" border="0" /></html>Previous entry<html>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;</html>

Simulating evolution and then pooled sequencing

  • We start with a population of N individuals with a certain SNP distribution [math]\displaystyle{ P(M) }[/math] ~ [math]\displaystyle{ N(\mu, \Sigma) }[/math].

To do this we can use Dick Hudson's MS to lay down neutral variants (but the distribution really does not matter).

  • We then evolve the populations for g generations with recombination

To do this we can use Kessner's Forqs. Forqs allows the user to specify the recombination rate file which might be useful in the future. Also Forqs was written in way with selection experiments in mind, they have functions such as "Quantitative Trait" that allows the user to define the fitness function in a complex way.

  • Simulate pooled sequencing

(1) draw a coverage (n) from [math]\displaystyle{ Pois(\lambda) }[/math] where [math]\displaystyle{ \lambda \approx 40-50 }[/math]

(2) [math]\displaystyle{ f_i }[/math] (frequency of the ith SNP) ~ [math]\displaystyle{ B(n, f_i^{true}) }[/math]