|
|
(132 intermediate revisions by 2 users not shown) |
Line 3: |
Line 3: |
|
| |
|
| The great thing about NGSadmix is that it is a new method that takes the uncertainty introduced in NGS sequencing data into account when inferring an individual's ancestry by using genotype likelihoods that considers the uncertainty caused by unobserved genotypes. | | The great thing about NGSadmix is that it is a new method that takes the uncertainty introduced in NGS sequencing data into account when inferring an individual's ancestry by using genotype likelihoods that considers the uncertainty caused by unobserved genotypes. |
| | |
| | As with the other existing software, ADMIXTURE and STRUCTURE, NGSadmix is only sensitive to admixture recent enough to cause structures in the population in terms of differing allele frequencies. Historical admixture events after which many generations has passed in the population, leaves no signature in terms of systematic differences in allele frequencies between individuals and are not a concern in association studies. |
|
| |
|
| [[File:NgsAdmix.png|thumb]] | | [[File:NgsAdmix.png|thumb]] |
Line 8: |
Line 10: |
| The method was published in 2013 and can be found here: [http://www.ncbi.nlm.nih.gov/pubmed/24026093] | | The method was published in 2013 and can be found here: [http://www.ncbi.nlm.nih.gov/pubmed/24026093] |
|
| |
|
| Citation: Skotte, L., Korneliussen, T. S., & Albrechtsen, A. (2013). Estimating individual admixture proportions from next generation sequencing data. Genetics, 195(3), 693–702. doi:10.1534/genetics.113.154138
| |
|
| |
|
| | ==Software Download== |
| | The latest version of NGSadmix is ngsadmix32 from June 25, 2013 and can be downloaded here: [http://popgen.dk/software/download/NGSadmix/ngsadmix32.cpp]. |
|
| |
|
| The latest version is 32 from June 25 2013 and can be downloaded here: [http://popgen.dk/software/download/NGSadmix/ngsadmix32.cpp ]. | | :'''Older Versions''' |
| | :The previous version of NGSadmix, ngsadmix31 can be found here: [http://popgen.dk/software/download/NGSadmix/ngsadmix31.cpp]. |
| | :Version Log: |
| | :* v32 june 25-2013; modified code such that it now compiles on OSX |
| | :* v31 june 24-2013; First public version. |
|
| |
|
| | ==Installation== |
|
| |
|
| Older versions can be found here:
| | NGSadmix can be installed independently or as a part of ANGSD. |
| [http://popgen.dk/software/download/NGSadmix/].
| |
|
| |
|
| =Installation= | | ====NGSadmix Independent Installation==== |
|
| |
|
| <pre> | | 1. Login to your server using ssh on your terminal window. |
| | |
| | 2. Create the directory where you will install your software and enter it, such as |
| | :<code>mkdir ~/Software</code> |
| | :<code>cd ~/Software</code> |
|
| |
|
| NGSadmix can be installed independently or as a part of ANGSD.
| | 3. Download the source code: |
| | :<code>wget https://raw.githubusercontent.com/ANGSD/angsd/master/misc/ngsadmix32.cpp </code> |
|
| |
|
| NGSadmix Independent Installation: | | 4. Configure, Compile and Install: |
| | :<code>g++ ngsadmix32.cpp -O3 -lpthread -lz -o NGSadmix</code> |
|
| |
|
| | ====NGSadmix Installation from ANGSD==== |
|
| |
|
| Login to your server using ssh on your terminal window.
| | :NGSadmix is part of the package ANGSD. To install ANGSD, please follow the instructions here [http://popgen.dk/angsd/index.php/Installation] |
| Create the directory where you will install your software and enter it, such as
| |
| mkdir ~/Software
| |
| cd ~/Software
| |
|
| |
|
| Download the source code:
| | ==Parameters== |
| wget https://raw.githubusercontent.com/ANGSD/angsd/master/misc/ngsadmix32.cpp
| |
|
| |
|
| Configure, Compile and Install:
| | All parameters are set using '''-par value'''. |
| g++ ngsadmix32.cpp -O3 -lpthread -lz -o NGSadmix
| | For example, to get additional information, you would write '''-printInfo 1'''. |
|
| |
|
| Delete source code to save space:
| | <pre>./NGSadmix </pre> |
| rm ~/Software/ngsadmix32.cpp
| |
|
| |
|
| | Arguments: |
|
| |
|
| | ::'''-likes''' .beagle format filename with genotype likelihoods |
|
| |
|
| </pre>
| | ::'''-K''' Number of ancestral populations |
|
| |
|
| =Brief Overview=
| |
| <div class="toccolours mw-collapsible mw-collapsed">
| |
| ./NGSadmix
| |
| <pre class="mw-collapsible-content">
| |
| Arguments:
| |
| -likes Beagle likelihood filename
| |
| -K Number of ancestral populations
| |
| Optional: | | Optional: |
| -fname Ancestral population frequencies
| |
| -qname Admixture proportions
| |
| -outfiles Prefix for output files
| |
| -printInfo print ID and mean maf for the SNPs that were analysed
| |
| Setup:
| |
| -seed Seed for initial guess in EM
| |
| -P Number of threads
| |
| -method If 0 no acceleration of EM algorithm
| |
| -misTol Tolerance for considering site as missing
| |
| Stop chriteria:
| |
| -tolLike50 Loglikelihood difference in 50 iterations
| |
| -tol Tolerance for convergence
| |
| -dymBound Use dymamic boundaries (1: yes (default) 0: no)
| |
| -maxiter Maximum number of EM iterations
| |
| Filtering
| |
| -minMaf Minimum minor allele frequency
| |
| -minLrt Minimum likelihood ratio value for maf>0
| |
| -minInd Minumum number of informative individuals
| |
| </pre>
| |
| </div>
| |
| NB All parameters are set using '''-par value'''. So to get additional information you would write '''-printInfo 1'''.
| |
|
| |
|
| =Run example=
| | ::'''-fname''' Ancestral population frequencies |
| First download some example test files which has been generated on basis of data from the 1000 genomes project (100 individuals from 5 populations with 50000 SNPs).
| | |
| <pre>
| | ::'''-qname''' Admixture proportions |
| wget popgen.dk/software/download/NGSadmix/data/input.gz
| |
| wget popgen.dk/software/download/NGSadmix/data/pop.info
| |
| </pre>
| |
|
| |
|
| We then have an input file called input.gz and assuming 3 ancestral populations (-K 3), and that we want to use 4 computing cores (-P 4). The prefix of the output files is myoutfiles (-o myoutfiles) using only SNP with af MAF above 5% (-minMaf 0.05).
| | ::'''-outfiles''' Prefix for output files |
|
| |
|
| <div class="toccolours mw-collapsible mw-collapsed">
| | ::'''-printInfo''' print ID and mean maximum allele frequency (maf) for the SNPs that were analysed |
| ./NGSadmix -likes input.gz -K 3 -P 4 -o myoutfiles -minMaf 0.05
| |
| <pre class="mw-collapsible-content">
| |
| -> Dumping file: myoutfiles.log
| |
| -> Dumping file: myoutfiles.filter
| |
| Input: lname=input.gz nPop=3, fname=(null) qname=(null) outfiles=myoutfiles
| |
| Setup: seed=1374071670 nThreads=4 method=1
| |
| Convergence: maxIter=2000 tol=0.000010 tolLike50=0.100000 dymBound=0
| |
| Filters: misTol=0.050000 minMaf=0.050000 minLrt=0.000000 minInd=0
| |
| Input file has dim: nsites=50000 nind=100
| |
| Input file has dim (AFTER filtering): nsites=49475 nind=100
| |
| iter[start] like is=6395247.407627
| |
| iter[50] like is=-3868746.751237 thres=0.002523
| |
| iter[100] like is=-3866294.760777 thres=0.003179
| |
| iter[150] like is=-3865984.169517 thres=0.000310
| |
| iter[200] like is=-3865965.879519 thres=0.000017
| |
| EM accelerated Thread has reached convergence with tol 0.000010
| |
| best like=-3865964.425455 after 245 iterations
| |
| -> Dumping file: myoutfiles.qopt
| |
| -> Dumping file: myoutfiles.fopt.gz
| |
| [ALL done] cpu-time used = 211.93 sec
| |
| [ALL done] walltime used = 105.00 sec
| |
|
| |
|
| </pre>
| | Setup: |
| </div>
| |
|
| |
|
| =Input Files=
| | ::'''-seed''' Seed for initial guess in EM algorithm (a number lower than 1M is preferred). |
| Input files are contains genotype likelihoods in genotype likelihood beagle input file format [http://faculty.washington.edu/browning/beagle/beagle.html]. We recommend [[ANGSD]] for easy transformation of Next-generation sequencing data to beagle format. See [http://www.popgen.dk/angsd/index.php/Beagle_input Creation of Beagle files with ANGSD]
| | :: The same seed can be used to reproduce the analysis, and 3 different seeds can be used to test convergence. |
|
| |
|
| Example of a beagle genotype likelihood input file for 3 individuals.
| | ::'''-P''' Number of threads |
| <pre>
| |
| marker allele1 allele2 Ind0 Ind0 Ind0 Ind1 Ind1 Ind1 Ind2 Ind2 Ind2
| |
| 1_14000023 1 0 0.941 0.058 0.000 0.799 0.199 0.001 0.666 0.333 0.001
| |
| 1_14000072 2 3 0.709 0.177 0.112 0.941 0.058 0.000 0.665 0.332 0.001
| |
| 1_14000113 0 2 0.855 0.106 0.037 0.333 0.333 0.333 0.799 0.199 0.000
| |
| 1_14000202 2 0 0.835 0.104 0.060 0.799 0.199 0.000 0.333 0.333 0.333
| |
| ...
| |
| </pre>
| |
| Column 1:The marker name (the information is not atually used)
| |
|
| |
|
| Column 2 and 3: the major and minor allele (these two columns are not used within the program and can contain whatever dummy value).
| | ::'''-method''' 0 indicates no acceleration of EM algorithm. Please refer to the paper for more information. |
|
| |
|
| The rest of the colums are the genotypes likelihoods (not in log space). For each individual we have 3 columns.
| | ::'''-misTol''' Tolerance for considering a site as missing. Default = 0.05. |
| Note that the above values sum to one per sites for each individuals. This is just a normalization of the genotype likelihoods in order to avoid underflow problems in the beagle software it does not mean that they are genotype probabilities.
| | :: To include high quality genotypes only, increase this value (for example, 0.9) |
|
| |
|
| The input file is allowed to be compressed with gzip.
| | Stop criteria: |
|
| |
|
| =Options=
| | ::'''-tolLike50''' Loglikelihood difference in 50 iterations. Default= 0.1 |
| <pre>
| |
| ./NGSadmix
| |
| Arguments:
| |
| -likes Beagle likelihood filename
| |
| -K Number of ancestral populations
| |
| Optional:
| |
| -fname Ancestral population frequencies
| |
| -qname Admixture proportions
| |
| -o Prefix for output files
| |
| -printInfo print ID and mean maf for the SNPs that were analysed
| |
| Setup:
| |
| -seed Seed for initial guess in EM
| |
| -P Number of threads
| |
| -method If 0 no acceleration of EM algorithm
| |
| -misTol Tolerance for considering site as missing
| |
| Stop chriteria:
| |
| -tolLike50 Loglikelihood difference in 50 iterations
| |
| -tol Tolerance for convergence
| |
| -dymBound Use dymamic boundaries (1: yes (default) 0: no)
| |
| -maxiter Maximum number of EM iterations
| |
| Filtering
| |
| -minMaf Minimum minor allele frequency
| |
| -minLrt Minimum likelihood ratio value for maf>0
| |
| -minInd Minumum number of informative individuals
| |
|
| |
|
| </pre> | | ::'''-tol''' Tolerance for convergence. Default = 1x10<sup>-5</sup>. Use maller values for higher accuracy. |
| | :: It's the maximum squared difference of F and Q (please refer to the paper for formula). |
|
| |
|
| =Output Files=
| | ::'''-dymBound''' Use dymamic boundaries (1: yes (default) 0: no). |
| Program outputs 3 files.
| |
|
| |
|
| # PREFIX.log
| |
| # PREFIX.fopt.gz
| |
| # PREFIX.qopt
| |
|
| |
|
| * 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.
| | ::'''-maxiter''' Maximum number of EM iterations. Default = 2000 (high value). |
| | :: In case it doesn't converge, this value needs to be higher. |
|
| |
|
| * The .fopt.gz file is an compressed file, which contains an estimate of the frequency for each site for all populations.
| | Filtering: |
|
| |
|
| * The .qopt file contains the admixture proportions for all individuals.
| | ::'''-minMaf''' Minimum minor allele frequency. Default = 5% |
|
| |
|
| Examples of the output files are found below.
| | ::'''-minLrt''' Minimum likelihood ratio value for maf>0. Default = 0 |
|
| |
|
| | ::'''-minInd''' Minumum number of informative individuals. Default = 0 |
| | :: It only keeps sites where there is at least x # of individuals with NGS data. |
|
| |
|
| ==Log file (.log)== | | ==Input File== |
| <div class="toccolours mw-collapsible mw-collapsed">
| |
| Contents of the file log file
| |
| <pre class="mw-collapsible-content">
| |
| -> Dumping file: tskSim/tsk6GL.beagle.s1.log
| |
| -> Dumping file: tskSim/tsk6GL.beagle.s1.filter
| |
| Input: lname=tskSim/tsk6GL.beagle nPop=3, fname=(null) qname=(null) outfiles=tskSim/tsk6GL.beagle.s1 | |
| Setup: seed=1 nThreads=10 method=1
| |
| Convergence: maxIter=2000 tol=0.000000 tolLike50=0.010000 dymBound=0
| |
| Filters: misTol=0.050000 minMaf=0.000000 minLrt=0.000000 minInd=0
| |
| Input file has dim: nsites=100000 nind=75
| |
| Input file has dim (AFTER filtering): nsites=100000 nind=75
| |
| iter[start] like is=9299805.984931
| |
| iter[50] like is=-6531138.892608 thres=0.002800
| |
| iter[100] like is=-6528710.773349 thres=0.001289
| |
| iter[150] like is=-6528405.896951 thres=0.001211
| |
| iter[200] like is=-6528306.803820 thres=0.000420
| |
| iter[250] like is=-6528277.160993 thres=0.000546
| |
| iter[300] like is=-6528271.925055 thres=0.000033
| |
| iter[350] like is=-6528271.177692 thres=0.000008
| |
| iter[400] like is=-6528270.876315 thres=0.000005
| |
| iter[450] like is=-6528270.772894 thres=0.000140
| |
| iter[500] like is=-6528270.747721 thres=0.000002
| |
| iter[550] like is=-6528270.740654 thres=0.000002
| |
| Convergence achived because log likelihooditer difference for 50 iteraction is less than 0.010000
| |
| best like=-6528270.740654 after 550 iterations
| |
| -> Dumping file: tskSim/tsk6GL.beagle.s1.qopt
| |
| -> Dumping file: tskSim/tsk6GL.beagle.s1.fopt.gz
| |
| [ALL done] cpu-time used = 671.82 sec
| |
| [ALL done] walltime used = 114.00 sec
| |
| </pre>
| |
| </div>
| |
|
| |
|
| ==Allele frequency ouput (.fopt)==
| | The input file contains genotype likelihoods in a .beagle file format [http://faculty.washington.edu/browning/beagle/beagle.html]. |
| Each column correponds to the estimated allele frequencies for each population and each line is a SNP
| | and can be compressed with gzip. |
| <div class="toccolours mw-collapsible mw-collapsed">
| | === BAM files === |
| Example of a .fopt file for -K 3
| | If you have BAM files you can use [[ANGSD]] to produce genotype likelihoods in .beagle format. Please |
| <pre class="mw-collapsible-content">
| | see [http://www.popgen.dk/angsd/index.php/Beagle_input Creation of Beagle files with ANGSD] |
| ... | |
| 0.75331646167520038837 0.51190946588401886608 0.50134051056701267601
| |
| 0.99999999900000002828 0.80165850924934911603 0.97470665326916294813
| |
| 0.99999999900000002828 0.89560828888972687789 0.88062641752218895341
| |
| 0.99999999900000002828 0.99999999900000002828 0.86109994249930577048
| |
| 0.70560445653074521655 0.78994686954000448154 0.93076614062025020413
| |
| 0.99999999900000002828 0.88878537780630872955 0.92662857068149151463
| |
| 0.05322676762098016434 0.22871739860812340117 0.17394852600322696645
| |
| 0.00000000100000000000 0.27428885137150410545 0.19029599645013275944
| |
| 0.57086006389212373691 0.42232596591112880891 0.74080063581586474974
| |
| 0.77359733910003525281 0.47380864146016693494 0.72073560889718923939
| |
| 0.49946404159405927148 0.21684946347150244050 0.15201985942558055021
| |
| 0.41802171086717271331 0.55490556205954566504 0.85691127728452165524
| |
| 0.77095213528720529794 0.60074618451005279418 0.70219544996184157792
| |
| 0.26517850405564091787 0.48500265408436060710 0.85432254709914456914
| |
| 0.80055081986260245852 0.74423201242010783574 0.87110476762969968334
| |
| 0.30563054476851375663 0.05233529475348827620 0.25911912824038613179
| |
| 0.51084997710733415222 0.62263692178557350498 0.50738250264097506381
| |
| 0.64790272562679740442 0.91230541484222271720 0.73015721390331478347
| |
| 0.07124629651164265942 0.37896482494356753534 0.29218012479334326548
| |
| 0.00000000100000000000 0.26969100790961914038 0.28395781874856029781
| |
| 0.97074775756045073027 0.79093498372643300520 0.64006920058897498471
| |
| 0.64661948716978157048 0.84130009558421925409 0.76730057769159087933
| |
| 0.86990900887920663553 0.79410745692063922085 0.69416721874359499367
| |
| 0.34956069940263900797 0.27773038429396151860 0.25923476721423144298
| |
| 0.77739744690560164120 0.51272232330145017798 0.53888718200036844763
| |
| 0.35431569298041332150 0.20022780744715171219 0.43176580786072032980
| |
| 0.91858160919413811563 0.99999999900000002828 0.93584179237779097082
| |
| 0.90339823126358831384 0.94729687041528465308 0.84358671720630329371
| |
| 0.87068129661127857677 0.65267891763324525911 0.59315740612546075106
| |
| 0.24102496839012735319 0.42777100607917967201 0.39594098602469629533
| |
| 0.99999999900000002828 0.99999999900000002828 0.78549330115836857313
| |
| 0.15386277372522660922 0.18035502891341426146 0.26583557049163752950
| |
| 0.22456748943597096280 0.25110807159057474403 0.17244618960511531869
| |
| 0.74816053649164548922 0.54769319158907958656 0.44532166240679449398
| |
| 0.76350303696805599252 0.86547244122202959815 0.94111974586621383043
| |
| 0.40940400475566068872 0.67767095908245833513 0.40793761498610620064
| |
| 0.85389765162910868934 0.78901563183853873351 0.93614065916219291186
| |
| 0.54108661985898742763 0.61895909938546000983 0.88522763262549941654
| |
| 0.99051495581855464323 0.78855843624128341141 0.77646441702623147929
| |
| 0.51133721761171413434 0.74521610846562824637 0.32689774480116673416
| |
| 0.66618479413060949224 0.67891474309775079465 0.80762116232856140385
| |
| 0.81793598261160704865 0.77752326447671193943 0.95349025244041396565
| |
| 0.82120324647844433752 0.99999999900000002828 0.89800731971059466474
| |
| ...
| |
| </pre>
| |
| </div>
| |
| Use the "-printInfo 1" option to get the position of the lines in the fopt file if some sites have been flltered from the analysis (-minMaf, minInd, minLRT etc)
| |
|
| |
|
| ==Admixture proportion output file (.qopt)== | | === VCF files === |
| Infered admixture proporsions. Each line is an individual and each column is a population.
| | If you already have made a VCF file that contains genotype likehood information then it should be possible to convert .vcf files with genotype likelihoods to .beagle file via vcftools [https://vcftools.github.io/man_latest.html] |
| <div class="toccolours mw-collapsible mw-collapsed">
| |
| Contents of the qopt file # cat tsk48GL.beagle.gz.s1.qopt
| |
| <pre class="mw-collapsible-content">
| |
| 0.00254460532103031574 0.00108987228478324210 0.99636552239418640919
| |
| 0.00000015905647541105 0.00000000100000000000 0.99999983994352459327
| |
| 0.00034770382567266174 0.02639209238328452459 0.97326020379104283275
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00000467398081877176 0.00000000100000000000 0.99999532501918120264
| |
| 0.00000000907496942853 0.00585150933779484805 0.99414848158723567728
| |
| 0.00515826525767644137 0.01138897436535154552 0.98345276037697204607
| |
| 0.03914841746468285949 0.00000000100000000000 0.96085158153531713410
| |
| 0.00000000100000000000 0.00629199375758324100 0.99370800524241675866
| |
| 0.00771173022930659625 0.00000154720357311662 0.99228672256712036059
| |
| 0.00000000100000000000 0.00075135345721917719 0.99924864554278081119
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000005468413042120 0.00087279924180633879 0.99912714607406327705
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00712941313019542066 0.00118955677574110528 0.99168103009406338710
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00165385222968000606 0.99834614677032007535
| |
| 0.00000000100000000000 0.00006297763597355473 0.99993702136402651259
| |
| 0.00519087111391381209 0.00000000100000000000 0.99480912788608621966
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00202872783596746379 0.00000000100000000000 0.99797127116403261393
| |
| 0.00876424336999809782 0.00949457841911990376 0.98174117821088191516
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.01820430093358888640 0.00000694033297829119 0.98178875873343274261
| |
| 0.00351013812443964728 0.00000020340562512923 0.99648965846993520223
| |
| 0.00771897550085272680 0.00605259705033356268 0.98622842744881378252
| |
| 0.00600595292580561029 0.00000000100000000000 0.99399404607419439284
| |
| 0.01454910070242997067 0.00543457657939076105 0.98001632271817917808
| |
| 0.02567862615486414535 0.00160921436783232220 0.97271215947730349516
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00000000100000000000 0.00001041560507852223 0.99998958339492149960
| |
| 0.00000000100000000000 0.01383432553657116572 0.98616567346342876021
| |
| 0.00343840097404925389 0.00000000100000000000 0.99656159802595079000
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00051244065751142103 0.00404846039501185508 0.99543909894747661937
| |
| 0.02003953974792894652 0.00000004934009128878 0.97996041091197982897
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999799999994554
| |
| 0.02176809890633762956 0.00000000100000000000 0.97823190009366245423
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.01563096189267457192 0.00970868396771427770 0.97466035413961116252
| |
| 0.00000000100000000000 0.00000000100000000000 0.99999999800000005656
| |
| 0.00002540964943070735 0.00000000100000000000 0.99997458935056915408
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99501476026684787524 0.00000000100000000000 0.00498523873315206718
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99520671498720802983 0.00479241730266987201 0.00000086771012207898
| |
| 0.95884374919730619435 0.00000000100000000000 0.04115624980269377842
| |
| 0.99002104218586972628 0.00000000100000000000 0.00997895681413022567
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999770925251941 0.00000000129074746013 0.00000000100000000000
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.98980053177767901573 0.00000005577971952226 0.01019941244260143612
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999785004878083416 0.00000000100000000000 0.00000214895121910354
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99220030909132039820 0.00000000100000000000 0.00779968990867968733
| |
| 0.99999996788621803301 0.00000000100000000000 0.00000003111378189772
| |
| 0.99736783433174225344 0.00255940950853666971 0.00007275615972113173
| |
| 0.99998096423035520708 0.00000000574461213317 0.00001903002503262207
| |
| 0.99711097909957713270 0.00288887008493822353 0.00000015081548462101
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99769262012085335734 0.00000000100000000000 0.00230737887914652393
| |
| 0.99999820787375570674 0.00000000433914936351 0.00000178778709493472
| |
| 0.98047422489554170166 0.00012980111977614777 0.01939597398468214523
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.98208006049140339488 0.00000000100000000000 0.01791993850859651197
| |
| 0.97530298545159921364 0.00000000100000000000 0.02469701354840085974
| |
| 0.99657542812406740840 0.00000000100000000000 0.00342457087593254226
| |
| 0.99954556420189066834 0.00045443479810919004 0.00000000100000000000
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99531584565237773976 0.00410740812985130408 0.00057674621777084644
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.99878572597704817770 0.00000000100000000000 0.00121427302295177490
| |
| 0.98571687209123504125 0.00400077401169816448 0.01028235389706666329
| |
| 0.99027397554762419674 0.00840892511494516215 0.00131709933743062008
| |
| 0.99999993504923445631 0.00000000100000000000 0.00000006395076564386
| |
| 0.95946639819101930957 0.00000000100000000000 0.04053360080898076034
| |
| 0.99999999800000005656 0.00000000100000000000 0.00000000100000000000
| |
| 0.98414939425022363029 0.01585059024074651421 0.00000001550902978739
| |
| 0.99999999622245250297 0.00000000277754757396 0.00000000100000000000
| |
| 0.99525652466242930938 0.00000001683386219288 0.00474345850370842034
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999999799999994554 0.00000000100000000000 0.00000000100000000000
| |
| 0.99999965447943561792 0.00000000100000000000 0.00000034452056438734
| |
| 0.99864814059528783652 0.00135185840471215468 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000001076370464123 0.99999998823629543399 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999999800000005656 0.00000000100000000000
| |
| 0.00000000100000000000 0.99999986659623718577 0.00000013240376283687
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000099999999999 0.99999999799999994554 0.00000000099999999999
| |
| 0.00000000100000000000 0.99632783404679736705 0.00367216495320256799
| |
| 0.00000000100000000000 0.99999999799999994554 0.00000000100000000000
| |
| 0.00000000099999999999 0.99999999800000005656 0.00000000099999999999
| |
| 0.35919621347731411909 0.32381633362411937904 0.31698745289856661289
| |
| 0.31048363757756514136 0.30902410742704566893 0.38049225499538924522
| |
| 0.36341140678787386964 0.33678307361394943520 0.29980551959817652863
| |
| 0.34550713774447228133 0.34037087985425079628 0.31412198240127681137
| |
| 0.34705579219215104692 0.35218792485566730033 0.30075628295218165276
| |
| 0.33646039412306782967 0.32632754139618752598 0.33721206448074481088
| |
| 0.31881401220765009930 0.34885621407165418040 0.33232977372069577582
| |
| 0.34999374672052624424 0.33030931848049555066 0.31969693479897826061
| |
| 0.33152251818028721786 0.32339147992992234304 0.34508600188979043910
| |
| 0.31959998197389311025 0.33152491237148390413 0.34887510565462298562
| |
| 0.34724548642936803322 0.31809475756470984020 0.33465975600592196004
| |
| 0.33378069767858009609 0.33223636639277298599 0.33398293592864686241
| |
| 0.32023090400419051971 0.33179989332826043125 0.34796920266754916007
| |
| 0.35205158009776410521 0.33547091017851976558 0.31247750972371612921
| |
| 0.34291063455495451873 0.31853488093100223999 0.33855448451404313026
| |
| 0.31929132670383747472 0.32755905579808902717 0.35314961749807355362
| |
| 0.34114474726121107873 0.34607065583774476725 0.31278459690104404300
| |
| 0.33725705347681012025 0.32910919226619778089 0.33363375425699209886
| |
| 0.33918213722968154622 0.32278745806952213737 0.33803040470079642743
| |
| 0.33788659799509024317 0.34692305448657090317 0.31519034751833896468
| |
| 0.35876135180876589370 0.33843260979944000955 0.30280603839179404124
| |
| 0.34721570614318736370 0.34395335873604998556 0.30883093512076259524
| |
| 0.34165097731337079612 0.32814110943000784903 0.33020791325662146587
| |
| 0.33922542743931027864 0.32639619830977489867 0.33437837425091476717
| |
| 0.34461619391735059947 0.33133174331942943924 0.32405206276321996128
| |
| 0.34277551565686120716 0.32746953398981676342 0.32975495035332202942
| |
| 0.33842982221926010133 0.31224638933762871584 0.34932378844311123833
| |
| 0.34443810815667752490 0.32640113997211872565 0.32916075187120380496
| |
| 0.31723258569943768581 0.34955203711397470068 0.33321537718658750249
| |
| 0.35394053250677920408 0.33291498389624818444 0.31314448359697255597
| |
| 0.33504517457864940733 0.34188143503173562543 0.32307339038961496724
| |
| 0.33240938202788244960 0.34671459781042585080 0.32087602016169164409
| |
| 0.31745792352948248860 0.33722730677636020280 0.34531476969415725309
| |
| 0.33098224522913716195 0.33312298285105168549 0.33589477191981131909
| |
| 0.34090909280056919117 0.32423671881295645925 0.33485418838647434958
| |
| 0.32985465610121944557 0.32124851771265583444 0.34889682618612483100
| |
| 0.33525528582568764335 0.31967441393853385234 0.34507030023577844879
| |
| 0.33823045943274382408 0.33932114218381809190 0.32244839838343819505
| |
| 0.34374166546335593875 0.33527470302709477812 0.32098363150954922762
| |
| 0.32177399566214615056 0.34277626859597382092 0.33544973574188002852
| |
| 0.34915111840878915173 0.33072079898488659921 0.32012808260632419355
| |
| 0.31132788816691708833 0.32844185942225745389 0.36023025241082540227
| |
| 0.33067206673512555826 0.34601992411426535368 0.32330800915060908807
| |
| 0.31337643746173032833 0.33835721859074846529 0.34826634394752131740
| |
| 0.32762993090356395953 0.34856645453438306337 0.32380361456205303261
| |
| 0.33558678075595765877 0.34449062515269568419 0.31992259409134682357
| |
| 0.33433652456352996873 0.32868556951924504661 0.33697790591722515119
| |
| 0.32115036446030281736 0.35050069566489522321 0.32834893987480190392
| |
| 0.32524569843140932468 0.33953480032298033464 0.33521950124561045170
| |
| 0.33520046917246110185 0.31124301814705779279 0.35355651268048110536
| |
| 0.51565151014669796670 0.00027180960956305278 0.48407668024373901039
| |
| 0.51978922685130035664 0.01333903580405943964 0.46687173734464021413
| |
| 0.48123878312258933088 0.00648941795451128591 0.51227179892289931296
| |
| 0.48941833241028537271 0.00512373007237581363 0.50545793751733880672
| |
| 0.48421136927686320162 0.00600153379448644612 0.50978709692865020742
| |
| 0.53246468447754891073 0.00000000100000000000 0.46753531452245111755
| |
| 0.50637710620505416159 0.01564455874020675985 0.47797833505473913407
| |
| 0.49416813414210103428 0.00000000100000000000 0.50583186485789899400
| |
| 0.51328206693115174808 0.00000000100000000000 0.48671793206884833571
| |
| 0.50420356848059588728 0.00779539942445491366 0.48800103209494921641
| |
| 0.51589943710654184716 0.00000000100000000000 0.48410056189345807010
| |
| 0.46643393286795947761 0.00024627960390510270 0.53331978752813535838
| |
| 0.50134326603627110686 0.00000000100000000000 0.49865673296372897694
| |
| 0.52516062216154979492 0.00887494007947397384 0.46596443775897622430
| |
| 0.50553300231497877437 0.00610541400596737328 0.48836158367905380118
| |
| 0.48505848053244243756 0.00412236953776635561 0.51081914992979127188
| |
| 0.50419106430093152404 0.00671707921410998055 0.48909185648495850929
| |
| 0.51266037905765671212 0.00565931340437971983 0.48168030753796364785
| |
| 0.50479638826213368841 0.00082364200405335279 0.49437996973381287402
| |
| 0.48963785250324892706 0.00000000100000000000 0.51036214649675115673
| |
| 0.49861342640726780129 0.00000000100000000000 0.50138657259273211597
| |
| 0.49321745088202589846 0.00000000100000000000 0.50678254811797418533
| |
| 0.52297921048641760056 0.00000000100000000000 0.47702078851358242773
| |
| 0.51351947193443381323 0.00000000100000000000 0.48648052706556610403
| |
| 0.49861600587139209839 0.01143470350387426789 0.48994929062473369097
| |
| 0.47497824395255133778 0.00413641430709298184 0.52088534174035572288
| |
| 0.50602874958787047444 0.00000013752429825494 0.49397111288783129845
| |
| 0.51347175918678078510 0.00477133273041653854 0.48175690808280269284
| |
| 0.50359809216181616875 0.00000002299679746021 0.49640188484138642044
| |
| 0.52201190781479689385 0.00000000100000000000 0.47798809118520296790
| |
| 0.52427554763933403859 0.01637369304678280152 0.45935075931388308357
| |
| 0.50464335890649447691 0.01062810063722730188 0.48472854045627822295
| |
| 0.48795095623978190780 0.00032508303858300066 0.51172396072163517378
| |
| 0.49273360783177866384 0.03185613233234574349 0.47541025983587564818
| |
| 0.49075081269029041664 0.00043182816413278401 0.50881735914557668643
| |
| 0.51236233643387329995 0.01050799870797843559 0.47712966485814828355
| |
| 0.51939186110717183720 0.00638063180499700081 0.47422750708783106832
| |
| 0.49685157861691658931 0.00000000100000000000 0.50314842038308338346
| |
| 0.50376251978896124939 0.00609062514993390959 0.49014685506110500235
| |
| 0.50469879197514677660 0.00000000100000000000 0.49530120702485330719
| |
| 0.48806858812981018803 0.00000000100000000000 0.51193141087018978475
| |
| 0.49345173654735252633 0.00767168036095551131 0.49887658309169191639
| |
| 0.51926063211476558568 0.00000000100000000000 0.48073936688523438709
| |
| 0.49182360714466144547 0.00000000100000000000 0.50817639185533869384
| |
| 0.50012065040991493525 0.00101172020552988784 0.49886762938455525562
| |
| 0.49490771372946151807 0.00000000100000000000 0.50509228527053839919
| |
| 0.50981594186492362741 0.01168450085559137597 0.47849955727948501050
| |
| 0.48459184220397827358 0.00000007440008454733 0.51540808339593724430
| |
| 0.51153925961371649045 0.00045999176804108893 0.48800074861824249695
| |
| 0.49380129779182529992 0.00214174101547949525 0.50405696119269527422
| |
| 0.10504303642339951619 0.45848347542219436423 0.43647348815440606407
| |
| 0.09383999674587484296 0.44580529318052469767 0.46035471007360045936
| |
| 0.11801124345951279071 0.44619343422410290279 0.43579532231638429263
| |
| 0.10150817897299509174 0.44474184109029252232 0.45374997993671234431
| |
| 0.14144944553914898244 0.47426718065022838156 0.38428337381062249722
| |
| 0.08656596263718574491 0.47201374694852676894 0.44142029041428754166
| |
| 0.10422682420288104099 0.45665008652196642513 0.43912308927515242285
| |
| 0.07422281507005458467 0.46668026430253822801 0.45909692062740725671
| |
| 0.11152984148911383733 0.44326164444242566187 0.44520851406846068121
| |
| 0.12101900721666984662 0.45534926548479054409 0.42363172729853953991
| |
| 0.19287147372937366030 0.40220634979635128126 0.40492217647427497518
| |
| 0.19868166550667537562 0.39952077624337684059 0.40179755824994778379
| |
| 0.20144056442189406386 0.40552701281654912613 0.39303242276155692103
| |
| 0.17400131741109717276 0.41572345587205422612 0.41027522671684846234
| |
| 0.19363830614785534912 0.39941552029693161430 0.40694617355521295332
| |
| 0.20932370419936904837 0.41063785306931777086 0.38003844273131326403
| |
| 0.21496306930156286463 0.41077627378883840858 0.37426065690959875454
| |
| 0.20887311245081657818 0.39219787302656328176 0.39892901452262014006
| |
| 0.18789467459437667052 0.42880445734573224836 0.38330086805989094234
| |
| 0.21467435158258502126 0.41396326091136687042 0.37136238750604805281
| |
| 0.30215275924600598634 0.35114326369103593395 0.34670397706295807971
| |
| 0.27985580964526363124 0.36766711333486662427 0.35247707701986974449
| |
| 0.29214764907998119758 0.34353124024041165052 0.36432111067960715189
| |
| 0.28098186396660507214 0.35436535705487937076 0.36465277897851555711
| |
| 0.29909659519210785028 0.34708664349540557792 0.35381676131248662731
| |
| 0.29960230758566036569 0.34764467237891033546 0.35275302003542929885
| |
| 0.28690707484319816212 0.36958476358894237768 0.34350816156785934918
| |
| 0.31218824558522878521 0.35988855578362860532 0.32792319863114272049
| |
| 0.29371283648699086921 0.34536893102077848017 0.36091823249223065062
| |
| 0.32028624797598659324 0.35059182523172049972 0.32912192679229296255
| |
| 0.39315538655109805166 0.30778919233772789044 0.29905542111117405790
| |
| 0.39625700997625840083 0.29350948690034872612 0.31023350312339292856
| |
| 0.40087160410050781678 0.31851581382017457589 0.28061258207931755182
| |
| 0.40117357253398744366 0.30569836130272198815 0.29312806616329067921
| |
| 0.40013703551439627759 0.28691859513594913933 0.31294436934965452757
| |
| 0.39131222513930874474 0.30759794867682349606 0.30108982618386764818
| |
| 0.40826221599444090238 0.30658973748486684219 0.28514804652069231095
| |
| 0.41420080477834714250 0.28227625784283560950 0.30352293737881719249
| |
| 0.39119930707342420728 0.32102763805993583812 0.28777305486664006562
| |
| 0.37635520411942069430 0.29805329179310008358 0.32559150408747933314
| |
| 0.51400585200303006150 0.26100245041580294458 0.22499169758116702167
| |
| 0.50336119658518030384 0.25110166586697690860 0.24553713754784287082
| |
| 0.47299237773462793344 0.26084178003823194070 0.26616584222714018138
| |
| 0.49359314224598493936 0.26013978211456978418 0.24626707563944530421
| |
| 0.52795469779405246324 0.26499345968140075591 0.20705184252454675309
| |
| 0.48219467330650939152 0.25987283477635270135 0.25793249191713785162
| |
| 0.47626160019217189667 0.25351817092177358903 0.27022022888605456981
| |
| 0.51617477226059282902 0.23162353057460718930 0.25220169716479995392
| |
| 0.49698887507445854705 0.24557159475841641716 0.25743953016712495252
| |
| 0.52733914260860248469 0.25309832534801629533 0.21956253204338116447
| |
| 0.56749881833694781896 0.19172441472755546998 0.24077676693549673881
| |
| 0.59339160859286765870 0.19241414198845174788 0.21419424941868048240
| |
| 0.62308540846251914136 0.18054125203843729430 0.19637333949904353658
| |
| 0.59485531592769125275 0.20909554531024135415 0.19604913876206744860
| |
| 0.61310545246842529377 0.20645329445333451823 0.18044125307824007698
| |
| 0.60102956519838679483 0.21237444166376903687 0.18659599313784405727
| |
| 0.59278179178128642679 0.20826418834431797977 0.19895401987439562119
| |
| 0.60456224253100432353 0.20686687908046738626 0.18857087838852840123
| |
| 0.59417710257213784963 0.21264514488765640099 0.19317775254020574938
| |
| 0.59059286756608764257 0.21451811369415349495 0.19488901873975889023
| |
| 0.69484036887292865980 0.14634823390637874407 0.15881139722069256837
| |
| 0.69945423984127830241 0.16333221995631252987 0.13721354020240922322
| |
| 0.69115689116107958956 0.14927316115273414621 0.15956994768618620872
| |
| 0.68851717088680941536 0.14201541767923545057 0.16946741143395496754
| |
| 0.69288781352263861812 0.14270021794166909412 0.16441196853569234326
| |
| 0.68819873910998985433 0.16242980538224471854 0.14937145550776548264
| |
| 0.68619763716276405141 0.14370194479775053042 0.17010041803948539041
| |
| 0.68596343194490616568 0.16051691534743553480 0.15351965270765843830
| |
| 0.70684340251150390433 0.16654037983665334610 0.12661621765184280508
| |
| 0.70657158115262697073 0.14984891346689468983 0.14357950538047842270
| |
| 0.79161214498168253062 0.10430887542937690438 0.10407897958894059276
| |
| 0.79477141808375573184 0.10274451187208989700 0.10248407004415439892
| |
| 0.80425538032447896342 0.10720945367236509038 0.08853516600315590457
| |
| 0.79445836435866723502 0.11481368508653701233 0.09072795055479568327
| |
| 0.80626524450581027459 0.08599284906042292675 0.10774190643376663212
| |
| 0.77991736902186048486 0.08777798585427237787 0.13230464512386716502
| |
| 0.77897241390666871474 0.11419808069913564563 0.10682950539419577840
| |
| 0.80225596727756287585 0.10739115862914316857 0.09035287409329402497
| |
| 0.81035643868218754093 0.11405964018980654928 0.07558392112800596530
| |
| 0.80474324803558927588 0.09992219310105134034 0.09533455886335934215
| |
| 0.89147290804053958002 0.05818869713285088757 0.05033839482660958098
| |
| 0.87135519951168793895 0.04885203404408157424 0.07979276644423052844
| |
| 0.90273220877706750187 0.05642671780738096193 0.04084107341555152232
| |
| 0.90299890240805003039 0.05982401615206547896 0.03717708143988454617
| |
| 0.88622329583732417646 0.03227381365259313073 0.08150289051008267893
| |
| 0.89149278212958615875 0.03556871666107842139 0.07293850120933542680
| |
| 0.90540444756330573650 0.06637446770308205735 0.02822108473361228942
| |
| 0.89581315874618450135 0.06675457610008654619 0.03743226515372900798
| |
| 0.86941364504212315101 0.03330392614486758773 0.09728242881300920575
| |
| 0.88098981477392690476 0.04673780362475228600 0.07227238160132080924
| |
| </pre>
| |
| </div>
| |
|
| |
|
| =Plot results=
| |
| Plot in the order of the input file.
| |
| <pre> | | <pre> |
| admix<-t(as.matrix(read.table("myoutfiles.qopt")))
| | vcftools --vcf input.vcf --out test --BEAGLE-GL --chr 1,2 |
| barplot(admix,col=1:3,space=0,border=NA,xlab="Individuals",ylab="admixture")
| |
| </pre> | | </pre> |
| [[File:NGSadmixEx1.png|frameless|600px]] | | Chromosome has to be specified. |
| | |
| | You can also use bcftools' [https://samtools.github.io/bcftools/bcftools.html] 'query' option for generating a .beagle file from a .vcf file. |
| | |
| | ==Output Files== |
| | The analysis performed by NGSadmix produces 4 files: |
| | |
| | * Log likelihood of the estimates: a .log file that summarizes the run. The Command line used for running the program, what the likelihood is every 50 iterations, and finally how long it took to do the run. |
| | |
| | * Estimated allele frequency: a zipped .fopt file, that contains an estimate of the allele frequency in each of the 3 assumed ancestral populations. There is a line for each locus. |
| | |
| | * Estimated admixture proportions: a .qopt file, that contains an estimate of the individual's ancestry proportion (admixture) from each of the three assumed ancestral populations for all individuals. There is a line for each individual. |
| | |
| | ==Run command example== |
| | |
| | Download the input file, for example |
| | ::<code>wget popgen.dk/software/download/NGSadmix/data/input.gz</code> |
| | |
| | Execute NGSadmix |
| | ::<code>./NGSadmix -likes input.gz -K 3 -P 4 -o myoutfiles -minMaf 0.05</code> |
| | |
| | ::* '''-likes''' Input .beagle file of genotype likelihoods = input.gz |
| | ::* '''-K''' Ancestral populations K=3 |
| | ::* '''-P''' Number of threads used, as computer cores = 4 |
| | ::* '''-o''' Output prefix, output file names = myoutfiles |
| | ::*'''-minMaf''' SNPs with MAF > 5% = 0.05 |
| | |
| | ===Detailed Examples and Tutorial=== |
|
| |
|
| | Please refer to the tutorial's page [http://www.popgen.dk/software/index.php/NgsAdmixTutorial] |
|
| |
|
| Plot using a population label file.
| | ==Citation== |
| <pre>
| |
| pop<-read.table("pop.info",as.is=T)
| |
| admix<-t(as.matrix(read.table("myoutfiles.qopt")))
| |
| admix<-admix[,order(pop[,1])]
| |
| pop<-pop[order(pop[,1]),]
| |
| h<-barplot(admix,col=1:3,space=0,border=NA,xlab="Individuals",ylab="admixture")
| |
| text(tapply(1:nrow(pop),pop[,1],mean),-0.05,unique(pop[,1]),xpd=T)
| |
| </pre>
| |
| [[File:NGSadmixEx2.png|frameless|600px]]
| |
|
| |
|
| =Citation=
| |
| http://www.genetics.org/content/early/2013/09/03/genetics.113.154138.full.pdf | | http://www.genetics.org/content/early/2013/09/03/genetics.113.154138.full.pdf |
| ==Bibtex==
| |
| <pre>
| |
| % 24026093
| |
| @Article{pmid24026093,
| |
| Author="Skotte, L. and Korneliussen, T. S. and Albrechtsen, A. ",
| |
| Title="{{E}stimating {I}ndividual {A}dmixture {P}roportions from {N}ext {G}eneration {S}equencing {D}ata}",
| |
| Journal="Genetics",
| |
| Year="2013",
| |
| Pages=" ",
| |
| Month="Sep"
| |
| }
| |
| </pre>
| |
|
| |
|
| =Log= | | Skotte, L., Korneliussen, T. S., & Albrechtsen, A. (2013). Estimating individual admixture proportions from next generation sequencing data. Genetics, 195(3), 693–702. doi:10.1534/genetics.113.154138 |
| * v32 june 25-2013; modified code such that it now compiles on OSX
| | |
| * v31 june 24-2013; First public version.
| | :<u>'''Bibtex'''</u> |
| | :% 24026093 |
| | :@Article{pmid24026093, |
| | : Author="Skotte, L. and Korneliussen, T. S. and Albrechtsen, A. ", |
| | : Title="{{E}stimating {I}ndividual {A}dmixture {P}roportions from {N}ext {G}eneration {S}equencing {D}ata}", |
| | : Journal="Genetics", |
| | : Year="2013", |
| | : Pages=" ", |
| | : Month="Sep" |
| | :} |