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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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|
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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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| * The log file contains log information of the run. Commandline used for running the program, what the likelihood is every 50 iterations, and finally how long it took to do the run.
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| * The fopt.gz file is an compressed file, which contains an estimate of the frequency for each site for all populations.
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| * The qopt file contains the admixture proportions for all individuals.
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| Examples of the output files are found below.
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| ==Log file==
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| <div class="toccolours mw-collapsible mw-collapsed">
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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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| ==fopt file==
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| <div class="toccolours mw-collapsible mw-collapsed">
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| Contents of the fopt file
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| <pre class="mw-collapsible-content">
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| ...
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| 0.75331646167520038837 0.51190946588401886608 0.50134051056701267601
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| 0.99999999900000002828 0.80165850924934911603 0.97470665326916294813
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| 0.99999999900000002828 0.89560828888972687789 0.88062641752218895341
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| 0.99999999900000002828 0.99999999900000002828 0.86109994249930577048
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| 0.70560445653074521655 0.78994686954000448154 0.93076614062025020413
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| 0.99999999900000002828 0.88878537780630872955 0.92662857068149151463
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| 0.05322676762098016434 0.22871739860812340117 0.17394852600322696645
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| 0.00000000100000000000 0.27428885137150410545 0.19029599645013275944
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| 0.57086006389212373691 0.42232596591112880891 0.74080063581586474974
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| 0.77359733910003525281 0.47380864146016693494 0.72073560889718923939
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| 0.49946404159405927148 0.21684946347150244050 0.15201985942558055021
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| 0.41802171086717271331 0.55490556205954566504 0.85691127728452165524
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| 0.77095213528720529794 0.60074618451005279418 0.70219544996184157792
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| 0.26517850405564091787 0.48500265408436060710 0.85432254709914456914
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| 0.80055081986260245852 0.74423201242010783574 0.87110476762969968334
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| 0.30563054476851375663 0.05233529475348827620 0.25911912824038613179
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| 0.51084997710733415222 0.62263692178557350498 0.50738250264097506381
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| 0.64790272562679740442 0.91230541484222271720 0.73015721390331478347
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| 0.07124629651164265942 0.37896482494356753534 0.29218012479334326548
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| 0.00000000100000000000 0.26969100790961914038 0.28395781874856029781
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| 0.97074775756045073027 0.79093498372643300520 0.64006920058897498471
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| 0.64661948716978157048 0.84130009558421925409 0.76730057769159087933
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| 0.86990900887920663553 0.79410745692063922085 0.69416721874359499367
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| 0.34956069940263900797 0.27773038429396151860 0.25923476721423144298
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| 0.77739744690560164120 0.51272232330145017798 0.53888718200036844763
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| 0.35431569298041332150 0.20022780744715171219 0.43176580786072032980
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| 0.91858160919413811563 0.99999999900000002828 0.93584179237779097082
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| 0.90339823126358831384 0.94729687041528465308 0.84358671720630329371
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| 0.87068129661127857677 0.65267891763324525911 0.59315740612546075106
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| 0.24102496839012735319 0.42777100607917967201 0.39594098602469629533
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| 0.99999999900000002828 0.99999999900000002828 0.78549330115836857313
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| 0.15386277372522660922 0.18035502891341426146 0.26583557049163752950
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| 0.22456748943597096280 0.25110807159057474403 0.17244618960511531869
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| 0.74816053649164548922 0.54769319158907958656 0.44532166240679449398
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| 0.76350303696805599252 0.86547244122202959815 0.94111974586621383043
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| 0.40940400475566068872 0.67767095908245833513 0.40793761498610620064
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| 0.85389765162910868934 0.78901563183853873351 0.93614065916219291186
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| 0.54108661985898742763 0.61895909938546000983 0.88522763262549941654
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| 0.99051495581855464323 0.78855843624128341141 0.77646441702623147929
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| 0.51133721761171413434 0.74521610846562824637 0.32689774480116673416
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| 0.66618479413060949224 0.67891474309775079465 0.80762116232856140385
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| 0.81793598261160704865 0.77752326447671193943 0.95349025244041396565
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| 0.82120324647844433752 0.99999999900000002828 0.89800731971059466474
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| ...
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| </pre>
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| </div>
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| There is currently no way to know the position of the lines of the fopt file if some sites have been flltered from the analysis (-minMaf, minInd, minLRT etc)
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| ==fopt file==
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| <div class="toccolours mw-collapsible mw-collapsed">
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| Contents of the qopt file # cat tsk3GL.beagle.s2.qopt
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| <pre class="mw-collapsible-content">
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| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
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| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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| 0.00000000099999999998 0.99999999799999994554 0.00000000099999999998
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| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
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| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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| 0.00000000099999999998 0.99999999800000005656 0.00000000099999999998
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| 0.00000000099999999998 0.99999999800000005656 0.00000000099999999998
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| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
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| 0.00000000099999999998 0.99999999799999994554 0.00000000099999999998
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
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| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
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| 0.00000000099999999999 0.00000000099999999999 0.99999999799999994554
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| 0.00000000099999999999 0.00000000099999999999 0.99999999800000005656
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| 0.00000000099999999998 0.00000000099999999998 0.99999999800000005656
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| 0.99999999799999994554 0.00000000099999999998 0.00000000099999999998
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| 0.99999999799999994554 0.00000000099999999999 0.00000000099999999999
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| 0.99999999800000005656 0.00000000099999999998 0.00000000099999999998
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| 0.99999999800000005656 0.00000000099999999999 0.00000000099999999999
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| 0.99999999799999994554 0.00000000099999999998 0.00000000099999999998
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| 0.99999999800000005656 0.00000000099999999997 0.00000000099999999997
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| 0.99999999799999994554 0.00000000099999999998 0.00000000099999999998
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| 0.99999999799999994554 0.00000000099999999998 0.00000000099999999998
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| 0.99999999800000005656 0.00000000099999999998 0.00000000099999999998
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| 0.99999999800000005656 0.00000000099999999998 0.00000000099999999998
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| 0.44943768488869317856 0.41637900975786718005 0.13418330535343961363
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| 0.47186367326154465829 0.42914964755124906937 0.09898667918720621683
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| 0.46619918726700892986 0.38687204966896221459 0.14692876306402888331
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| 0.46354437118930408301 0.40881857587008219035 0.12763705294061369888
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| 0.45264535107721121099 0.41651331006337249940 0.13084133885941623410
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| 0.40932662855941681634 0.36477521833198955914 0.22589815310859343023
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| 0.39608002688940713298 0.36869218630330241604 0.23522778680729045098
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| 0.39304099203400788554 0.36663653899437026462 0.24032246897162179433
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| 0.39911937105983025242 0.37389960053391524397 0.22698102840625450360
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| 0.39092771268619924685 0.35969519959821749655 0.24937708771558322884
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| 0.34274262701666824427 0.33331325906604786224 0.32394411391728383798
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| 0.34622392335992407952 0.31117372685925065445 0.34260234978082515500
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| 0.36985984530580445773 0.28437303864342194926 0.34576711605077359302
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| 0.34804143030185941132 0.33320171229649653277 0.31875685740164411142
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| 0.32407237526064275324 0.34027116723473044280 0.33565645750462674846
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| 0.28469849506708616582 0.30226647920831278826 0.41303502572460099040
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| 0.31135738016083241986 0.28468835604445524856 0.40395426379471233158
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| 0.30218663019413083415 0.25900355534445085315 0.43880981446141842373
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| 0.31011059343113106523 0.27004727407307288489 0.41984213249579616090
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| 0.29539308688690751881 0.26676206410012109904 0.43784484901297143766
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| 0.25367119636935991922 0.23716915741045718757 0.50915964622018294872
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| 0.24505013582826862262 0.26225101108896364810 0.49269885308276778479
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| 0.23718598793000850167 0.27299881774859108274 0.48981519432140036008
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| 0.24951870566854128519 0.24237250904076637625 0.50810878529069236631
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| 0.23352168811501466950 0.27256392034385162892 0.49391439154113375709
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| 0.22072760551069600665 0.18807146366485538724 0.59120093082444857835
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| 0.20165105305591241036 0.21322142854316492033 0.58512751840092280808
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| 0.19519805052535590950 0.15138471360822350342 0.65341723586642053156
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| 0.19534378883681183248 0.20162790752303333397 0.60302830364015480580
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| 0.20238951172887570396 0.22222668638306158906 0.57538380188806270699
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| 0.15279240264333296406 0.14309387185793090436 0.70411372549873607607
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| 0.16100786962332866437 0.13804093967765596052 0.70095119069901545839
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| 0.15236995575600070785 0.15690823378806481592 0.69072181045593450399
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| 0.13511175034410827234 0.17826273138113590822 0.68662551827475581945
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| 0.15053185641660885019 0.13684961152751642932 0.71261853205587477600
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| 0.08227475031000705541 0.11820319734260385791 0.79952205234738904505
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| 0.10752144811289739146 0.10824453011896040255 0.78423402176814216435
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| 0.05058595423834794796 0.13728840870228020687 0.81212563705937179659
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| 0.08815267889176078842 0.15395244513438488543 0.75789487597385429840
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| 0.10406527302537364743 0.09764688441014507392 0.79828784256448126477
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| 0.04451783049237752893 0.00000000100000000000 0.95548216850762246466
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| 0.00159304110901842245 0.00000000100000000000 0.99840695789098143909
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| 0.02104265004540380873 0.10109817256862485557 0.87785917738597141202
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| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
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| 0.00000075082077831480 0.00121780838207670200 0.99878144079714503700
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| </pre>
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| </div>
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| =Plot results=
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| Use R
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| <pre>
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| admix<-t(as.matrix(read.table("tsk48GL.beagle.gz.s1.qopt")))
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| barplot(admix,col=1:3,space=0,border=NA,xlab="Individuals",ylab="admixture")
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| </pre>
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| [[File:wikires2.png|frameless|600px]]
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| ----
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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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