Body: <p>What is the state-of-the-art to obtain SNVs from circulating tumor DNA after Illumina sequencing? This is, finding a list of nucleotide locations that show tumour SNVs filtered out of any germline polymorphisms.</p>
  
  <p>Found so far:</p>
  
  <ul>
  <li><p><a href="https://www.ncbi.nlm.nih.gov/pubmed/27531099" rel="nofollow noreferrer" title="article">SiNVICT: ultra-sensitive detection of single nucleotide variants and
  indels in circulating tumour DNA.</a></p></li>
  <li><p><a href="https://github.com/OpenGene/ctdna-pipeline" rel="nofollow noreferrer" title="code">OpenGene/ctdna-pipeline</a></p></li>
  <li><p><a href="https://github.com/mikessh/mageri" rel="nofollow noreferrer" title="code">MAGERI</a>: <a href="http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005480" rel="nofollow noreferrer" title="article">article</a></p></li>
  <li><p><a href="https://github.com/broadinstitute/mutect" rel="nofollow noreferrer" title="code">MuTect</a>: running it against a synthetic normal for unmatched cfDNA samples that don't have normal, then filtering for 1000G germline mutations.</p></li>
  <li><p><a href="https://github.com/cancerit/CaVEMan" rel="nofollow noreferrer" title="code">CaVEMan</a>: running it against a reference normal for unmatched cfDNA samples that don't have equivalent normal, then filtering for 1000G germline mutations.</p></li>
  <li><p><a href="http://bioconductor.org/packages/ShearWater" rel="nofollow noreferrer" title="Bioconductor">ShearWater</a>: <a href="https://bioconductor.org/packages/3.7/bioc/vignettes/deepSNV/inst/doc/shearwaterML.html" rel="nofollow noreferrer" title="vignette">corrects against germline mutations by training against a set of healthy normal samples.</a></p></li>
  </ul>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-03-28T07:30:08.163Z
Comments.Text: Do you think you can narrow a bit more? In what aspects are you interested? What tool(s) have you tried?
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-03-28T08:13:43.410Z
Comments.Text: @Llopis I have now extended the question and added 3 more pieces of software that I found relevant.
Comments.UserDisplayName: 719016
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-03-28T08:26:40.220Z
Comments.Text: Yes, precisely because you can grow the list *ad infinitum* I wanted you to narrow the question. In general those open ended questions don't work well in the StackExchange format because they don't have an answerable with a correct answer. And tend to results in a list of software, that although interesting and useful it might fit better for a blog or other type of resources. That's why I asked if you have some problem with any of these tools.
Comments.UserDisplayName: llrs
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2018-03-28T08:34:40.263Z
Comments.Text: The problem is that, presumably, all of these are "state of the art", so choosing one will be largely a question of opinion. Therefore, this is a very interesting discussion, but not really something that can be given a definitive answer of the sort that the Stack Exchange model requires.
Comments.UserDisplayName: terdon
Tags: <snv>
Title: state-of-the-art methods to obtain SNVs from circulating tumor DNA?
ThreadText: # state-of-the-art methods to obtain SNVs from circulating tumor DNA?
  
  (Asked by: username_0 on 2018-03-28)
  
  What is the state-of-the-art to obtain SNVs from circulating tumor DNA after Illumina sequencing? This is, finding a list of nucleotide locations that show tumour SNVs filtered out of any germline polymorphisms.
  
  Found so far:
  
  * [SiNVICT: ultra-sensitive detection of single nucleotide variants and
    indels in circulating tumour DNA.](https://www.ncbi.nlm.nih.gov/pubmed/27531099 "article")
  * [OpenGene/ctdna-pipeline](https://github.com/OpenGene/ctdna-pipeline "code")
  * [MAGERI](https://github.com/mikessh/mageri "code"): [article](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1005480 "article")
  * [MuTect](https://github.com/broadinstitute/mutect "code"): running it against a synthetic normal for unmatched cfDNA samples that don't have normal, then filtering for 1000G germline mutations.
  * [CaVEMan](https://github.com/cancerit/CaVEMan "code"): running it against a reference normal for unmatched cfDNA samples that don't have equivalent normal, then filtering for 1000G germline mutations.
  * [ShearWater](http://bioconductor.org/packages/ShearWater "Bioconductor"): [corrects against germline mutations by training against a set of healthy normal samples.](https://bioconductor.org/packages/3.7/bioc/vignettes/deepSNV/inst/doc/shearwaterML.html "vignette")
  
  **Tags:** snv
  
  > **Comments:**
  > **username_1**: Do you think you can narrow a bit more? In what aspects are you interested? What tool(s) have you tried?  
  > **username_0**: @Llopis I have now extended the question and added 3 more pieces of software that I found relevant.  
  > **username_1**: Yes, precisely because you can grow the list *ad infinitum* I wanted you to narrow the question. In general those open ended questions don't work well in the StackExchange format because they don't have an answerable with a correct answer. And tend to results in a list of software, that although interesting and useful it might fit better for a blog or other type of resources. That's why I asked if you have some problem with any of these tools.  
  > **username_2**: The problem is that, presumably, all of these are "state of the art", so choosing one will be largely a question of opinion. Therefore, this is a very interesting discussion, but not really something that can be given a definitive answer of the sort that the Stack Exchange model requires.  
  
  ---
  
  ## 0 answers
  
  