text: user57: I have estimated genome-wide heterozygosity levels using maximum likelihood and classical substitution model implemented in package atlas. These estimates are way more robust than classical SNP calling and simply counting number of heterogeneous locations because they integrate information from a big window into one estimate. I.e. I am quite sure about heterozygosity levels of SNPs of my genomes.
  However, now I would like to know also about heterozygosity of indels and call individual snps using my robust estimates as a prior. GATK allows to specify priors on heterozygosity both of SNPs and indels, which might improve variant calls a lot, because default GATK is parametrised for human (Default priors for heterozygous SNPs is 0.001 and for indel 1.25E-4.). But, I work with insects I know that my SNPs heterozygosity is somewhere between 0.01 and 0.03 (1% - 3%).
  So here comes the question, if I know the heterozygosity of SNPs, can I simply guess a reasonable prior for the heterozygosity of indels? GATK defaults for priors are 10x different, should I assume the same relation? Is there a reasonable way how to guess a prior for heterozygosity of indels?
  
  user492: SNPs, insertions, and deletions are generated by different biological processes (see for example here). I would expect the per-generation rates of these mutational processes to vary across species. I would also expect the degree to which each mutational process varies across species to vary as well. I think the answer to your question is "probably not without further information".
  However, priors are a feature of Bayesian statistics. In Bayesian inference, it is good practice to redo one's analysis using several priors to establish how sensitive one's results are to the chosen prior. I would suggest that you try to call indels using a range of priors and compare the quality of your call sets to determine how important the choice of prior actually is. 
  
original_text: 57: <p>I have estimated genome-wide heterozygosity levels using maximum likelihood and classical substitution model implemented in package <a href="https://bitbucket.org/WegmannLab/atlas/wiki/Home" rel="nofollow noreferrer">atlas</a>. These estimates are way more robust than classical SNP calling and simply counting number of heterogeneous locations because they integrate information from a big window into one estimate. I.e. I am quite sure about heterozygosity levels of SNPs of my genomes.</p>
  
  <p>However, now I would like to know also about heterozygosity of indels and call individual snps using my robust estimates as a prior. GATK allows to specify priors on heterozygosity both of SNPs and indels, which might improve variant calls a lot, because default GATK is parametrised for human (Default priors for heterozygous SNPs is 0.001 and for indel 1.25E-4.). But, I work with insects I know that my SNPs heterozygosity is somewhere between 0.01 and 0.03 (1% - 3%).</p>
  
  <p>So here comes the question, if I know the heterozygosity of SNPs, can I simply guess a reasonable prior for the heterozygosity of indels? GATK defaults for priors are 10x different, should I assume the same relation? Is there a reasonable way how to guess a prior for heterozygosity of indels?</p>
   492: <p>SNPs, insertions, and deletions are generated by different biological processes (see for example <a href="https://en.wikipedia.org/wiki/Mutation_rate#Variation_in_mutation_rates" rel="nofollow noreferrer">here</a>). I would expect the per-generation rates of these mutational processes to vary across species. I would also expect the degree to which each mutational process varies across species to vary as well. I think the answer to your question is "probably not without further information".</p>
  
  <p>However, priors are a feature of Bayesian statistics. In Bayesian inference, it is good practice to redo one's analysis using several priors to establish how sensitive one's results are to the chosen prior. I would suggest that you try to call indels using a range of priors and compare the quality of your call sets to determine how important the choice of prior actually is. </p>
  