<p>I am attempting to call mutations of raw RNA-Seq of single prostate circulating tumor cells (<a href="http://science.sciencemag.org/content/349/6254/1351.abstract">paper</a>) without matching normals.</p>

<p>From cursory research I found that tumor only without a matched normal calls 117x more variants than matched tumor/normal pairs (<a href="http://www.appistry.com/2014/mutect-tumor-samples-vs-tumornormal-matched-pairs/">Appistry</a>). I also found an interesting study that (successfully) discriminated somatic and germline mutations without matching normals but using <em>virtual </em><em>normal </em>(i.e., normal samples from unrelated individuals) (<a href="https://www.ncbi.nlm.nih.gov/pubmed/26209359">paper</a>).</p>

<p>My question is, are blood tumor samples treated any differently than tissue tumor samples in respect to calling variants? If there are no normal blood samples available, is filtering against the EVS dataset my best option? Thank you for your time and help.</p>

Some of this has been covered in previous questions on here (dig around a little), but the gist is this

 - you will never get rid of all germline mutations without a matched normal.
 - make sure your variant caller is appropriate and doesn't bias you towards mutations at 50%/100% VAF, as some germline callers can
 - a panel of normals can be very helpful in filtering out both common population variants and sequencing artifacts. Every individual contains private rare mutations that will ultimately be indistinguishable from a somatic hit, though.
 - yes, use EVS (or maybe even the non-TCGA-derived part of ExAC) to remove common variants.
 - RNAseq complicates things even further, because you're dealing with an enhanced error rate.