text: user6776: We know that in next-generation sequencing (NGS), the unique molecular identifier (UMI) can reduce or eliminate sequencing or PCR errors and result in very high accurate data. Therefore, UMI is widely used in rare mutation detection. A typical application is cancer early detection or minimal residual disease (MRD) detection that try to find the very rare DNA from cancer cells in the blood.
  However, we also know that the cell-free DNA in the blood is very low, typically 5 ng in 1 mL blood. And it usually takes about 10 mL blood to get about 50 ng DNA to get sequenced with UMI. Limited DNA input leads to many false negatives.
  So I came up with an idea: What if I got a sample with plenty of DNA? Can I detect rare mutations using UMI in this sample?
  The UMI library preparation protocols I have met all use a small amount of DNA input, say 50ng. If I have 1μg DNA, do I have to cut it to 50ng to prepare the UMI library?
  
  user3848: The question is
  
  "Do I add 20-fold more DNA than the kit states?"
  
  Its not my area - this is wet-lab - but there will be a tolerance however 20-fold is excessive (>1 log), i.e. no it doesn't help and could cause (expensive) downstream problems. The people to contact are the support for the given kit, there are unlikely to support your idea.
  The answer isn't wet-lab but almost certainly is bioinformatics and detecting low frequency somatic driver mutations. The Broad Institute worked on this problem for years, its nothing new, i.e. identifying driver mutations in highly mixed sample comprising healthy somatic tissue and cancer cells.
  I've tracked their work and have a reasonable understanding of what they do and why: oncology isn't my field. Your in-house bioinformatician should know this stuff.
  One suggest is using MuTect from the Broad Institute, I assume there have been many custom solutions since then. Their famous product is GATK for VCF, I don't think thats the solution here.
  Again cancer isn't my area BTW this is just common knowledge within bioinformatics, i.e. knowing what someone else is doing and why is part of the knowledge base.
  Please do try to retain a bioinformatics focus for future questions.
  
  user15710: Whole genome sequencing uses between 50 ng and 1 μg of high-quality DNA (A260/A280: 1.7–2.0) for PCR-amplified or non-amplified libraries if your focus is precision oncology as described in the following open access review in Seminars in Cancer Biology paper by Meggendorfer et al 2022
  
original_text: 6776: <p>We know that in next-generation sequencing (NGS), the unique molecular identifier (UMI) can reduce or eliminate sequencing or PCR errors and result in very high accurate data. Therefore, UMI is widely used in rare mutation detection. A typical application is cancer early detection or minimal residual disease (MRD) detection that try to find the very rare DNA from cancer cells in the blood.</p>
  <p>However, we also know that the cell-free DNA in the blood is very low, typically 5 ng in 1 mL blood. And it usually takes about 10 mL blood to get about 50 ng DNA to get sequenced with UMI. Limited DNA input leads to many false negatives.</p>
  <p>So I came up with an idea: <strong>What if I got a sample with plenty of DNA? Can I detect rare mutations using UMI in this sample?</strong></p>
  <p>The UMI library preparation protocols I have met all use a small amount of DNA input, say 50ng. <strong>If I have 1μg DNA, do I have to cut it to 50ng to prepare the UMI library?</strong></p>
   3848: <p>The question is</p>
  <blockquote>
  <p>&quot;Do I add 20-fold more DNA than the kit states?&quot;</p>
  </blockquote>
  <p>Its not my area - <em>this is wet-lab</em> - but there will be a tolerance however 20-fold is excessive (&gt;1 log), i.e. no it doesn't help and could cause (expensive) downstream problems. The people to contact are the support for the given kit, there are unlikely to support your idea.</p>
  <p>The answer isn't wet-lab but almost certainly is bioinformatics and detecting low frequency somatic driver mutations. The Broad Institute worked on this problem for years, its nothing new, i.e. identifying driver mutations in highly mixed sample comprising healthy somatic tissue and cancer cells.</p>
  <p>I've tracked their work and have a reasonable understanding of what they do and why: oncology isn't my field. Your in-house bioinformatician should know this stuff.</p>
  <p>One suggest is using <a href="https://software.broadinstitute.org/cancer/cga/mutect" rel="nofollow noreferrer">MuTect</a> from the Broad Institute, I assume there have been many custom solutions since then. Their famous product is GATK for VCF, I don't think thats the solution here.</p>
  <p>Again cancer isn't my area BTW this is just common knowledge within bioinformatics, i.e. knowing what someone else is doing and why is part of the knowledge base.</p>
  <p>Please do try to retain a bioinformatics focus for future questions.</p>
   15710: <p>Whole genome sequencing uses between 50 ng and 1 μg of high-quality DNA (A260/A280: 1.7–2.0) for PCR-amplified or non-amplified libraries if your focus is precision oncology as described in the following open access review in <a href="https://drive.google.com/file/d/1sRrhn_oCpf1cxnFshPl0-7XGjtZAkUfm/view?usp=sharing" rel="nofollow noreferrer">Seminars in Cancer Biology paper by Meggendorfer <em>et al</em> 2022</a></p>
  