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Bayesdenovo (view source)

Revision as of 12:30, 25 October 2016

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== Filtering ==
 
== Filtering ==
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We recommend two filtering strategies. The first is a simple filtering and the second one is more advance
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We recommend two filtering strategies. The first is a simple filtering and the second one is more advance. Please see the triodenovo page below for more information:
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1. Basic filtering for SNVs. The following filter will retain sites of single nucleotides with only two alleles, QUAL>=30, and mutations in which parents are homozygous references and child is heterozygote with the heterozygote PL being zero, and the minimum PL of the other two genotypes in offering is 30 (i.e. the genotype likelihood, defined as P(R|G) in which R represents the aligned bases and G is the underlying genotype, of the called het mutation is >1000 than the genotype likelihood of the other two genotypes). These filtering parameters can be tuned as needed in the following command.
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http://genome.sph.umich.edu/wiki/Triodenovo
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less trio.vcf.out | egrep "DQ|#" | perl -lane 'print if /#/; next if length($F[3])>1 || length($F[4])>1 || $F[4]=~/,/; next if $F[5]<30; $F[9] =~ /([A-Z])\/([A-Z])/; next if $1 ne $2; next if $F[10] !~ /$1\/$1/; $F[11]=~/([A-Z])\/([A-Z])/; next if $1 eq $2; $F[11] =~ /(\d+),(\d+),(\d+)/; next if $2 != 0 || $1<30 || $3<30; print' | less
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2. Advanced filtering using a machine-learning approach (i.e. DNMFilter in the following webpage)
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http://humangenome.duke.edu/software
      
3. Further thoughts about filtering for SNVs without bam files (step 2 requires bam files). There is no consensus on filtering so this can be very flexible.
 
3. Further thoughts about filtering for SNVs without bam files (step 2 requires bam files). There is no consensus on filtering so this can be very flexible.
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== Download ==
 
== Download ==
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Source code of v0.05 [[Media:triodenovo.0.05.tar.gz | download]] here.
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Source code of v0.01 [[Media:bayesdenovo.0.01.tar.gz | download]] here.
    
== Contact ==
 
== Contact ==
 
For questions please contact the authors (Bingshan Li:  [mailto:bingshan.li@vanderbilt.edu bingshan.li@vanderbilt.edu])
 
For questions please contact the authors (Bingshan Li:  [mailto:bingshan.li@vanderbilt.edu bingshan.li@vanderbilt.edu])
Bingshan
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