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PCAdapt is a population genetics software that jointly learns population structure and detects markers involved in local adaptation. It implements the MCMC algorithm to solve the matrix factorization model. It also includes a fast version to apply when dozens of millions of markers are in the dataset.

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duforetn/PCAdapt

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Welcome to the first version of PCAdapt. genotype file must contain snps in rows and individuals in column. values are noted with 0, 1, 2 or 9 in case of missing data.

  1. To compile type: $> make lapack $> make

  2. To run PCAdapt: $> ./PCAdapt //will display the manual if compilation went OK $> ./PCAdapt -i Example/Data4pops_1 -o My4popsResults -K 5 -b 100 -s 200 //Will run an example with 400 individuals in 4 pops, and 8000 independent snps, where 400 of them are under selection.

  3. To run FastPCAdapt $> ./PCAdapt fast //will display the manual if compilation went OK $> ./PCAdapt fast -i Example/Data4pops_1 Example/Data4pops_2 -o My4popsResults -K 3 //Will run an example with 400 individuals in 4 pops, and 10000 independent snps in two different files, where 400 of them are under selection.

  4. To clean your folder from executable files: $> make clean // removes the files in obj and PCAdapt $> make realclean // removes the files in obj, obj_lapack, and PCAdapt

version 05/26/14: Computations of Bayes Factors, Posterior Odds, and conditionnal probabilities. Enhanced SVD initialisation. Potts model. Use of different values of Ck. scaling of the variables by default. Version of Fast PCAdapt!

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PCAdapt is a population genetics software that jointly learns population structure and detects markers involved in local adaptation. It implements the MCMC algorithm to solve the matrix factorization model. It also includes a fast version to apply when dozens of millions of markers are in the dataset.

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