Answers.Body: <p>I've been using the <a href="http://csb5.github.io/lofreq/" rel="nofollow noreferrer" title="LoFreq*">LoFreq* caller</a> for exactly this. It is designed to find variants with very low frequency, so is well suited for this type of analysis.</p>
  <blockquote>
  <p>LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.</p>
  <p>LoFreq* is very sensitive; most notably, it is able to predict variants below the average base-call quality (i.e. sequencing error rate). Each variant call is assigned a p-value which allows for rigorous false positive control. Even though it uses no approximations or heuristics, it is very efficient due to several runtime optimizations and also provides a (pseudo-)parallel implementation.</p>
  </blockquote>
  <p>(In my experience it is not fast at all, but that's what they claim).</p>
  <p>I have used it many times to call somatic variants using the germline caller (and not its somatic one which requires a tumor/normal pair). Because the tool is so sensitive, its germline caller actually deals quite well with somatic samples.</p>
  <p>You can find instructions for its use <a href="http://csb5.github.io/lofreq/commands/" rel="nofollow noreferrer" title="Commands for LoFreq*">here</a>.</p>
  
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Answers.Text: I have used LoFreq as well and think it does a good job.  It is very sensitive and almost always requires some post filtering to get a reasonable number of calls.  One hazard I have found with its model is that if the variant is actually the majority call at the position it can have trouble reporting it.  This can happen with samples that have a large tumor cellularity.
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Answers.Text: @Bioathlete oh? Thanks, that's good to know!
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Answers.Body: <blockquote>
    <p>All the popular variant calling tools such as Strelka, VarScan etc
    require a normal sample.</p>
  </blockquote>
  
  <p>Strelka and VarScan require a normal sample in somatic mode, but they both have a germline mode for unpaired analysis.</p>
  
  <p>One of the most popular somatic variant callers is MuTect and that does not require a normal.</p>
  
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Answers.Body: <p>There is a <a href="https://www.ncbi.nlm.nih.gov/pubmed/28659176" rel="noreferrer">recent paper</a> that attempts to do this:</p>
  
  <blockquote>
    <p>ISOWN: accurate somatic mutation identification in the absence of
    normal tissue controls.</p>
    
    <p>In this work, we describe the development, implementation, and
    validation of ISOWN, an accurate algorithm for predicting somatic
    mutations in cancer tissues in the absence of matching normal tissues.
    ISOWN is available as Open Source under Apache License 2.0 from
    <a href="https://github.com/ikalatskaya/ISOWN" rel="noreferrer">https://github.com/ikalatskaya/ISOWN</a></p>
  </blockquote>
  
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Body: <p>I'm evaluating possibilites for somatic tumor variant calling without paired-normal samples. I'm aware of the consequences without a normal sample.</p>
  
  <p>All the popular variant calling tools such as Strelka, VarScan etc require a normal sample.</p>
  
  <p>What are the some of the possibilites I have? I'm looking for good sensitivity in exchange for higher false positives.</p>
  
Tags: <variant-calling><cancer><genomics>
Title: Somatic tumor only variant calling?
ThreadText: # Somatic tumor only variant calling?
  
  (Asked by: username_0 on 2017-10-31)
  
  I'm evaluating possibilites for somatic tumor variant calling without paired-normal samples. I'm aware of the consequences without a normal sample.
  
  All the popular variant calling tools such as Strelka, VarScan etc require a normal sample.
  
  What are the some of the possibilites I have? I'm looking for good sensitivity in exchange for higher false positives.
  
  **Tags:** variant-calling, cancer, genomics
  
  
  ---
  
  ## 3 answers
  
  ### Answer by username_4 on 2017-11-01. Score: 5 | Accepted answer
  
  There is a [recent paper](https://www.ncbi.nlm.nih.gov/pubmed/28659176) that attempts to do this:
  
  > ISOWN: accurate somatic mutation identification in the absence of
  > normal tissue controls.
  >
  > In this work, we describe the development, implementation, and
  > validation of ISOWN, an accurate algorithm for predicting somatic
  > mutations in cancer tissues in the absence of matching normal tissues.
  > ISOWN is available as Open Source under Apache License 2.0 from
  > <https://github.com/ikalatskaya/ISOWN>
  
  
  ---
  
  ### Answer by username_1 on 2017-11-01. Score: 5
  
  I've been using the [LoFreq\* caller](http://csb5.github.io/lofreq/ "LoFreq*") for exactly this. It is designed to find variants with very low frequency, so is well suited for this type of analysis.
  
  > LoFreq\* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.
  >
  > LoFreq\* is very sensitive; most notably, it is able to predict variants below the average base-call quality (i.e. sequencing error rate). Each variant call is assigned a p-value which allows for rigorous false positive control. Even though it uses no approximations or heuristics, it is very efficient due to several runtime optimizations and also provides a (pseudo-)parallel implementation.
  
  (In my experience it is not fast at all, but that's what they claim).
  
  I have used it many times to call somatic variants using the germline caller (and not its somatic one which requires a tumor/normal pair). Because the tool is so sensitive, its germline caller actually deals quite well with somatic samples.
  
  You can find instructions for its use [here](http://csb5.github.io/lofreq/commands/ "Commands for LoFreq*").
  
  > **Comments:**
  > **username_2**: I have used LoFreq as well and think it does a good job.  It is very sensitive and almost always requires some post filtering to get a reasonable number of calls.  One hazard I have found with its model is that if the variant is actually the majority call at the position it can have trouble reporting it.  This can happen with samples that have a large tumor cellularity.  
  > **username_1**: @username_2 oh? Thanks, that's good to know!  
  
  ---
  
  ### Answer by username_3 on 2017-11-07. Score: 2
  
  > All the popular variant calling tools such as Strelka, VarScan etc
  > require a normal sample.
  
  Strelka and VarScan require a normal sample in somatic mode, but they both have a germline mode for unpaired analysis.
  
  One of the most popular somatic variant callers is MuTect and that does not require a normal.
  
  
  ---
  
  