RelateAdmix: Difference between revisions

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../src/relateAdmix -plink smallPlink -f smallPlink.2.P -q smallPlink.2.Q -P 20
../src/relateAdmix -plink smallPlink -f smallPlink.2.P -q smallPlink.2.Q -P 20
</pre>
</pre>
=== output file ===
example of output
<pre>
ind1    ind2    k0      k1      k2      nIter
0      1      0.999941        0.000038        0.000021        26
0      2      0.999979        0.000010        0.000011        29
0      3      0.999953        0.000029        0.000018        26
0      4      0.999952        0.000023        0.000025        26
0      5      0.999972        0.000020        0.000007        26
0      6      0.999995        0.000003        0.000002        26
0      7      0.999995        0.000003        0.000002        26
0      8      0.999894        0.000069        0.000038        32
0      9      0.999894        0.000069        0.000038        32
0      10      0.999903        0.000071        0.000026        26
0      11      0.999903        0.000071        0.000026        26
</pre>
The first two columns are the individuals number. The next three columns are the estimated relatedness coefficients and the last column is the number of iterations used

Revision as of 14:47, 21 August 2013

Brief description

This page contains information about the program called relateAdmix, which can be used to infer relatedness coefficients for pairs of individuals even if they are admixed. The program has both an R interface and a C interface. Below is a description of how to install and use each of them. To be able to infer the relatedness you will need to know the individuals admixture proportions and the allele frequencies in each of the possible populations. This can be done e.g. using the program Admixture as shown in the example of how to use the C interface.

Installation

Download

Download folder

Installation of R package

wget http://www.popgen.dk/software/download/relateAdmix/relateAdmix_0.05.tar.gz
R CMD INSTALL relateAdmix_0.05.tar.gz


Installation of C program

wget http://www.popgen.dk/software/download/relateAdmix/relateAdmix_0.05.tar.gz
tar -xvzf relateAdmix_0.05.tar.gz 
cd relateAdmix/src/ 
mv CPP_Makefile Makefile
make

Run example

Run example using R

After installing the package you can load it into R and try the example

library(relateAdmix)
example(relate)

This shows an example of how to use the package. More information can be found in the man pages

?relate


Run example using C

After installing the program you can try running it on the example data set in the data folder, which consists of 50 individuals that are admixed from 2 source populations.

If you are in the src folder where you installed relateAdmix and you have the software Admixture installed this can be done as follows:

cd ../data

# First run Admixture to produce population specific allele frequencies (smallPlink.2.P) 
# and individual ancestry proportions (smallPlink.2.Q).
# (note other programs can also be used, e.g. Structure and FRAPPE)
admixture smallPlink.bed 2 

# Then run relateAdmix
../src/relateAdmix -plink smallPlink -f smallPlink.2.P -q smallPlink.2.Q -P 20

output file

example of output

ind1    ind2    k0      k1      k2      nIter
0       1       0.999941        0.000038        0.000021        26
0       2       0.999979        0.000010        0.000011        29
0       3       0.999953        0.000029        0.000018        26
0       4       0.999952        0.000023        0.000025        26
0       5       0.999972        0.000020        0.000007        26
0       6       0.999995        0.000003        0.000002        26
0       7       0.999995        0.000003        0.000002        26
0       8       0.999894        0.000069        0.000038        32
0       9       0.999894        0.000069        0.000038        32
0       10      0.999903        0.000071        0.000026        26
0       11      0.999903        0.000071        0.000026        26


The first two columns are the individuals number. The next three columns are the estimated relatedness coefficients and the last column is the number of iterations used