text: user10296: I have a vcf info formatted in GT:PL.
  chr22  49994037    .   G   A   345.64  PASS    AC=1;AF=0.500;AN=2;BaseQRankSum=-3.605;DP=35;ExcessHet=3.0103;FS=1.377;MLEAC=1;MLEAF=0.500;MQ=60.00;MQRankSum=0.000;QD=10.17;ReadPosRankSum=-0.035;SOR=0.392    GT:AD:DP:GQ:PL  0/1:20,14:34:99:353,0,588
  I want to convert it into GT:GP. But I have to write a script for that. Is there any way to do it fast and simple?
  Note:
  GT:Genotype
  PL: Phred-scaled Genotype Likelihoods
  GP: Genotype Probabilities
  check the link below for all the info tags
  https://samtools.github.io/hts-specs/VCFv4.2.pdf
  
  user3694: Currently you have phred-scaled genotype likelihoods or PL values. Genotype likelihoods give the likelihood of observing the read data (i.e. the number of reads which map to either the ref or alt allele), given a particular underlying genotype (0/0, 0/1, 1/1 at a bi-allelic locus); $GL = p(G|D)$. Phred scaling simply scales it like $PL = -10 * log(GL)$. These are usually given by a genotype caller.
  Genotype probabilities are slightly different in that they are posterior probabilities that the genotype is correct, given either other genotypes from a population or trio and a prior distribution for the allele frequencies. Therefore, you can't trivially go from likelihoods to probabilities without accounting for this external information and the prior. As suggested by JRodrigoF, you should use something like CalculateGenotypePosteriors to do this, maybe including 1000 genomes allele counts.
  
original_text: 10296: <p>I have a vcf info formatted in GT:PL.</p>
  <p><code>chr22  49994037    .   G   A   345.64  PASS    AC=1;AF=0.500;AN=2;BaseQRankSum=-3.605;DP=35;ExcessHet=3.0103;FS=1.377;MLEAC=1;MLEAF=0.500;MQ=60.00;MQRankSum=0.000;QD=10.17;ReadPosRankSum=-0.035;SOR=0.392    GT:AD:DP:GQ:PL  0/1:20,14:34:99:353,0,588</code></p>
  <p>I want to convert it into GT:GP. But I have to write a script for that. Is there any way to do it fast and simple?</p>
  <p>Note:</p>
  <p>GT:Genotype</p>
  <p>PL: Phred-scaled Genotype Likelihoods</p>
  <p>GP: Genotype Probabilities</p>
  <p>check the link below for all the info tags</p>
  <p><a href="https://samtools.github.io/hts-specs/VCFv4.2.pdf" rel="nofollow noreferrer">https://samtools.github.io/hts-specs/VCFv4.2.pdf</a></p>
   3694: <p>Currently you have <strong>phred-scaled genotype likelihoods</strong> or <strong>PL</strong> values. Genotype likelihoods give the likelihood of observing the read data (i.e. the number of reads which map to either the ref or alt allele), given a particular underlying genotype (0/0, 0/1, 1/1 at a bi-allelic locus); <span class="math-container">$GL = p(G|D)$</span>. Phred scaling simply scales it like <span class="math-container">$PL = -10 * log(GL)$</span>. These are usually given by a genotype caller.</p>
  <p><strong>Genotype probabilities</strong> are slightly different in that they are posterior probabilities that the genotype is correct, given either other genotypes from a population or trio and a prior distribution for the allele frequencies. Therefore, you can't trivially go from likelihoods to probabilities without accounting for this external information and the prior. As suggested by JRodrigoF, you should use something like <a href="https://gatk.broadinstitute.org/hc/en-us/articles/360036730531-CalculateGenotypePosteriors" rel="nofollow noreferrer">CalculateGenotypePosteriors</a> to do this, maybe including 1000 genomes allele counts.</p>
  