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| This will contain the program called NGSadmix, which is a very nice tool for finding admixture. It is based on genotype likelihoods or genotype probabilities.
| | NGSadmix is a tool for estimating individual admixture proportions low depth sequencing data based on genotype likelihoods |
| It is a fancy multithreaded c/c++ program
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| =Installation=
| | The software including tutorials can be found here |
| | | https://github.com/aalbrechtsen/NGSadmix |
| <pre>
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| wget popgen.dk/software/NGSadmix/ngsadmix32.cpp
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| g++ ngsadmix32.cpp -O3 -lpthread -lz -o NGSadmix
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| </pre>
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| =Input Files=
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| The current input files are the widely used beagle inputfiles, or beagle imputed outputfiles [http://faculty.washington.edu/browning/beagle/beagle.html]. We recommend [[ANGSD]] for easy transformation of Next-generation sequencing data to beagle format.
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| =Options=
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| <pre>
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| ./NGSadmix
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| Arguments:
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| -likes Beagle likelihood filename
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| -K Number of ancestral populations
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| Optional:
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| -fname Ancestral population frequencies
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| -qname Admixture proportions
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| -outfiles Prefix for output files
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| -printInfo print ID and mean maf for the SNPs that were analysed
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| Setup:
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| -seed Seed for initial guess in EM
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| -P Number of threads
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| -method If 0 no acceleration of EM algorithm
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| -misTol Tolerance for considering site as missing
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| Stop chriteria:
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| -tolLike50 Loglikelihood difference in 50 iterations
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| -tol Tolerance for convergence
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| -dymBound Use dymamic boundaries (1: yes (default) 0: no)
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| -maxiter Maximum number of EM iterations
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| Filtering
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| -minMaf Minimum minor allele frequency
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| -minLrt Minimum likelihood ratio value for maf>0
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| -minInd Minumum number of informative individuals
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| </pre>
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| =Output Files=
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| Program outputs 3 files.
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| # PREFIX.log
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| # PREFIX.fopt.gz
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| # PREFIX.qopt
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| ==Log file==
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| Contents of the file log file
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| <pre class="mw-collapsible-content">
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| -> Dumping file: tskSim/tsk6GL.beagle.s1.log
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| -> Dumping file: tskSim/tsk6GL.beagle.s1.filter
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| Input: lname=tskSim/tsk6GL.beagle nPop=3, fname=(null) qname=(null) outfiles=tskSim/tsk6GL.beagle.s1
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| Setup: seed=1 nThreads=10 method=1
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| Convergence: maxIter=2000 tol=0.000000 tolLike50=0.010000 dymBound=0
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| Filters: misTol=0.050000 minMaf=0.000000 minLrt=0.000000 minInd=0
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| Input file has dim: nsites=100000 nind=75
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| Input file has dim (AFTER filtering): nsites=100000 nind=75
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| iter[start] like is=9299805.984931
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| iter[50] like is=-6531138.892608 thres=0.002800
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| iter[100] like is=-6528710.773349 thres=0.001289
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| iter[150] like is=-6528405.896951 thres=0.001211
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| iter[200] like is=-6528306.803820 thres=0.000420
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| iter[250] like is=-6528277.160993 thres=0.000546
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| iter[300] like is=-6528271.925055 thres=0.000033
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| iter[350] like is=-6528271.177692 thres=0.000008
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| iter[400] like is=-6528270.876315 thres=0.000005
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| iter[450] like is=-6528270.772894 thres=0.000140
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| iter[500] like is=-6528270.747721 thres=0.000002
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| iter[550] like is=-6528270.740654 thres=0.000002
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| Convergence achived because log likelihooditer difference for 50 iteraction is less than 0.010000
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| best like=-6528270.740654 after 550 iterations
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| -> Dumping file: tskSim/tsk6GL.beagle.s1.qopt
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| -> Dumping file: tskSim/tsk6GL.beagle.s1.fopt.gz
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| [ALL done] cpu-time used = 671.82 sec
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| [ALL done] walltime used = 114.00 sec
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| </pre>
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| </div>
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| =log=
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| * v32 june 25-2013; modified code such that it now compiles on OSX
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| * v31 june 24-2013; First public version.
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