Answers.Body: <p>I cannot think of any principled rationale for choosing this filtering strategy. </p>
  
  <p>However, I am going to take a guess that this filtering strategy is supposed to filter out SNPs for which imputation did not work well?  In that case the appropriate statistic to filter on is the INFO score as described <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html#data_summaries" rel="nofollow noreferrer">here</a>.</p>
  
  <p>You might consider picking a higher threshold than 0.4 if you feel that you aren't filtering out enough variants.</p>
  
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Answers.CreationDate: 2017-06-04T23:11:39.370Z
Answers.LastActivityDate: 2018-01-16T21:12:58.123Z
Answers.LastEditDate: 2018-01-16T21:12:58.123Z
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Body: <p>There are many posts on the web regarding QC steps pre and post-imputation.</p>
  
  <p>Does applying below (new?) 10% <a href="https://en.wikipedia.org/wiki/Minor_allele_frequency" rel="nofollow noreferrer">MAF</a> difference rule make sense, pitfalls?</p>
  
  <p>Here is the process:</p>
  
  <ol>
  <li>Get MAF for imputed set, using <a href="https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html" rel="nofollow noreferrer">SNPTEST</a> with flag <code>-summary_stats_only</code></li>
  <li>Convert imputed set to hard-calls using <a href="http://www.well.ox.ac.uk/~cfreeman/software/gwas/gtool.html" rel="nofollow noreferrer">gtools</a> with flag <code>--threshold 0.9</code></li>
  <li>If the MAF from step 1 and step 2 differs more than 10% than exclude the variant.</li>
  </ol>
  
  <p>More info:</p>
  
  <ul>
  <li>GWAS is 50K vs 50K case control samples.</li>
  <li>This step is applied after <code>info &gt; 0.4</code> filter.</li>
  </ul>
  
Tags: <gwas><imputation><qc>
Title: Filtering imputed GWAS SNPs based on a MAF difference of 10%
ThreadText: # Filtering imputed GWAS SNPs based on a MAF difference of 10%
  
  (Asked by: username_0 on 2017-05-31)
  
  There are many posts on the web regarding QC steps pre and post-imputation.
  
  Does applying below (new?) 10% [MAF](https://en.wikipedia.org/wiki/Minor_allele_frequency) difference rule make sense, pitfalls?
  
  Here is the process:
  
  1. Get MAF for imputed set, using [SNPTEST](https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html) with flag `-summary_stats_only`
  2. Convert imputed set to hard-calls using [gtools](http://www.well.ox.ac.uk/~cfreeman/software/gwas/gtool.html) with flag `--threshold 0.9`
  3. If the MAF from step 1 and step 2 differs more than 10% than exclude the variant.
  
  More info:
  
  * GWAS is 50K vs 50K case control samples.
  * This step is applied after `info > 0.4` filter.
  
  **Tags:** gwas, imputation, qc
  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2017-06-04. Score: 3
  
  I cannot think of any principled rationale for choosing this filtering strategy.
  
  However, I am going to take a guess that this filtering strategy is supposed to filter out SNPs for which imputation did not work well? In that case the appropriate statistic to filter on is the INFO score as described [here](https://mathgen.stats.ox.ac.uk/genetics_software/snptest/snptest.html#data_summaries).
  
  You might consider picking a higher threshold than 0.4 if you feel that you aren't filtering out enough variants.
  
  
  ---
  
  