text: user-1: I have annotated files from annvar and I changed them into MAF by using
  annovarToMaf from ‘maftools’. Then I used read.maf to read them into R and then I used merge_mafs to integrate them together inside the last file.
  I had several data frames but it separated the synonymous mutations (maf.silent) from the non-synonymous mutations, and I want to create an oncoplot using the oncoplot function for both synonymous mutations from the non-synonymous mutations.
  But once I use this command I don't know how to integrate both data frames inside of the MAF file.
  How can I create the oncoplot using oncoplot for both synonymous mutations and non-synonymous mutations?
  
  user14020: This is late but I am putting it here for future reference. You can use the vc_nonsyn argument in the read.maf function to manually list the variant classifications you want to plot later. It will look like this:
  df.maf <- read.maf(maf = df, vc_nonSyn = c("Frame_Shift_Del","Missense_Mutation","Nonstop_Mutation","Silent","Splice_Region"))
  
  
original_text: -1: <p>I have annotated files from annvar and I changed them into MAF by using
  <code>annovarToMaf</code> from <a href="https://bioconductor.org/packages/release/bioc/html/maftools.html" rel="nofollow noreferrer">‘maftools’</a>. Then I used <code>read.maf</code> to read them into R and then I used <code>merge_mafs</code> to integrate them together inside the last file.</p>
  <p>I had several data frames but it separated the synonymous mutations (<code>maf.silent</code>) from the non-synonymous mutations, and I want to create an oncoplot using the <code>oncoplot</code> function for both synonymous mutations from the non-synonymous mutations.</p>
  <p>But once I use this command I don't know how to integrate both data frames inside of the MAF file.</p>
  <p>How can I create the oncoplot using <code>oncoplot</code> for both synonymous mutations and non-synonymous mutations?</p>
   14020: <p>This is late but I am putting it here for future reference. You can use the <code>vc_nonsyn</code> argument in the <code>read.maf</code> function to manually list the variant classifications you want to plot later. It will look like this:</p>
  <pre><code>df.maf &lt;- read.maf(maf = df, vc_nonSyn = c(&quot;Frame_Shift_Del&quot;,&quot;Missense_Mutation&quot;,&quot;Nonstop_Mutation&quot;,&quot;Silent&quot;,&quot;Splice_Region&quot;))
  </code></pre>
  