NgsAdmix: Difference between revisions

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Assuming we have an input file called input.gz and we assume 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)
Assuming we have an input file called input.gz and we assume 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)
<pre>
<pre>
./ngsAdmix -likes input.gz -K 3 -P 4 -tol 0.00000001 -tolLike50 0.01 -o myoutfiles -minMaf 0.05  
./NGSadmix -likes input.gz -K 3 -P 4 -tol 0.00000001 -tolLike50 0.01 -o myoutfiles -minMaf 0.05  
</pre>
</pre>



Revision as of 14:13, 17 July 2013

This will contain the program called NGSadmix, which is a very nice tool for finding admixture. It is based on genotype likelihoods. It is a fancy multithreaded c/c++ program.


Latest version is 32 from June 25 2013. It can be found [1]. Older versions can be found here: [2]

Installation

wget popgen.dk/software/NGSadmix/ngsadmix32.cpp 
g++ ngsadmix32.cpp -O3 -lpthread -lz -o NGSadmix

Run example

Assuming we have an input file called input.gz and we assume 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)

./NGSadmix -likes input.gz -K 3 -P 4 -tol 0.00000001 -tolLike50 0.01 -o myoutfiles -minMaf 0.05 

Input Files

Input files are contains genotype likelihoods in beagle input file format [3]. We recommend ANGSD for easy transformation of Next-generation sequencing data to beagle format.

Options

./NGSadmix
Arguments:
	-likes Beagle likelihood filename
	-K Number of ancestral populations
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

Output Files

Program outputs 3 files.

  1. PREFIX.log
  2. PREFIX.fopt.gz
  3. 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.
  • The fopt.gz file is an compressed file, which contains an estimate of the frequency for each site for all populations.
  • The qopt file contains the admixture proportions for all individuals.

Examples of the output files are found below.


Log file

Contents of the file log file

	-> 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

fopt file

Contents of the fopt file

...
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 
...

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)

qopt file

Contents of the qopt file # cat tsk48GL.beagle.gz.s1.qopt

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 
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0.31745792352948248860 0.33722730677636020280 0.34531476969415725309 
0.33098224522913716195 0.33312298285105168549 0.33589477191981131909 
0.34090909280056919117 0.32423671881295645925 0.33485418838647434958 
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0.33525528582568764335 0.31967441393853385234 0.34507030023577844879 
0.33823045943274382408 0.33932114218381809190 0.32244839838343819505 
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0.32177399566214615056 0.34277626859597382092 0.33544973574188002852 
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Plot results

Use R

admix<-t(as.matrix(read.table("tsk48GL.beagle.gz.s1.qopt")))
barplot(admix,col=1:3,space=0,border=NA,xlab="Individuals",ylab="admixture")

citation

log

  • v32 june 25-2013; modified code such that it now compiles on OSX
  • v31 june 24-2013; First public version.