ANGSD: Analysis of next generation Sequencing Data

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Beagle input: Difference between revisions

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In this example our input files are bam files. We use the samtools genotype likelihood methods. We use 10 threads. We infer the major and minor allele from the likelihoods and estimate the allele frequencies. We test for polymorphic sites and only output the ones with are likelhood ratio test  p-value<1e-6.  
In this example our input files are bam files. We use the samtools genotype likelihood methods. We use 10 threads. We infer the major and minor allele from the likelihoods and estimate the allele frequencies. We test for polymorphic sites and only output the ones with are likelhood ratio test  p-value<1e-6.  
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./angsd -GL 1 -out genolike -nThreads 10 -doGlf 2 -doMajorMinor 3 -SNP_pval 1e-6 -doMaf 2  -bam bam.filelist -sites reduced.bim
./angsd -GL 1 -out genolike -nThreads 10 -doGlf 2 -doMajorMinor 1 -SNP_pval 1e-6 -doMaf 2  -bam bam.filelist
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Revision as of 14:20, 6 March 2014

Beagle haplotype imputation can be performed directly on genotype likelihoods. To generate beagle input file use

-doGlf 2

In order to make this file the major and minor allele has the be inferred (-doMajorMinor) and genotype likelihoods need to be estimated (-GL) . It is also a good idea to only use the polymorphic sites, see Filters and SNP_calling.


Example

In this example our input files are bam files. We use the samtools genotype likelihood methods. We use 10 threads. We infer the major and minor allele from the likelihoods and estimate the allele frequencies. We test for polymorphic sites and only output the ones with are likelhood ratio test p-value<1e-6.

./angsd -GL 1 -out genolike -nThreads 10 -doGlf 2 -doMajorMinor 1 -SNP_pval 1e-6 -doMaf 2  -bam bam.filelist

output

The above command generates the file genolike.beagle.gz that can be use as input for the beagle software

marker  allele1 allele2 Ind0    Ind0    Ind0    Ind1    Ind1    Ind1    Ind2    Ind2    Ind2    Ind3    Ind3    Ind3 
1_14000023      1       0       0.941177        0.058822        0.000001        0.799685        0.199918        0.000397        0.666316        0.333155        0.000529 
1_14000072      2       3       0.709983        0.177493        0.112525        0.941178        0.058822        0.000000        0.665554        0.332774        0.001672
1_14000113      0       2       0.855993        0.106996        0.037010        0.333333        0.333333        0.333333        0.799971        0.199989        0.000040 
1_14000202      2       0       0.835380        0.104420        0.060201        0.799685        0.199918        0.000397        0.333333        0.333333        0.333333
...

Note that the above values sum to one per site 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.

The imputation can be done in beagle using the command

java -Xmx15000m -jar beagle.jar like=genolike.beagle.gz out=beagleOutName

Beagle outputs phasing and genotype probabilities. These can be using in ANGSD for downstream analysis such as MAF estimation and Association testing