Recently I read an article titled with "A Composite of Multiple Signals Distinguishes Causal Variants in Regions of Positive Selection". http://www.sciencemag.org/content/327/5967/883.abstract
I tried to implement the CMS but met some troubles.
what do the simulation work for? Was it used to distinguish the selected and non-selected region?
I saw lots of parameters in its supplementary, and I tried to use those parameters in cosi( a simulator ).However, I do not know how to add the additional parameter to get the different results. Besides, I don't understand how to judge whether the simulation works well or not. Which result of simulation is compared with real data, the neutral one or the selected one?
About the program they released at http://www.broadinstitute.org/scientific-community/science/programs/medical-and-population-genetics/cms/code. As I know little about python, I fail to run it, even the example pyTestCMS.py in the program.
Please help!
In the article there are different kinds of simulation, based on one Neutral model, I think. The simulation generate 100 replicas per scenario, and then add one additional parameter to generate calibrated model. There are 90 different parameters, so there produce 90 different results. So I'm not sure how to judge whether the simulation is good or not. There's only one real data but 90 or 91 different simulation results.