Genomic Precision

 A SeraCare blog focused on precision medicine and advanced clinical diagnostics

Next-Generation QC Precision Metrics for Next-Generation Sequencing

Introducing the SeraCare Confidence Score, a comprehensive precision metric designed for NGS assays

Posted by Lorn Davis on Apr 16, 2018 4:00:00 PM


There is an even greater onus to track quality control metrics for NGS assays because of the number of steps and elements that must successfully work together to produce consistent results. The Standards and Guidelines for Validating NGS Bioinformatics, published in January by AMP and CAP, highlight the importance of tracking QC metrics over time because “trends in these metrics can indicate an emerging issue with an NGS process that has not yet manifested itself in failed tests.”

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Topics: NGS assays, QC Challenges, NGS Management Software, QC Management Software, bioinformatics, Quality Management Systems, Clinical NGS Assays, qc management, confidence score, SeraCare Confidence Score

This is the Number One Risk to Your Clinical Sequencing Assay

Critical missteps during the assay development phase can cause expensive delays and risk the quality of an assay. How can you be sure your bioinformatics pipeline is correctly calling variants?

Posted by Trevor Brown on Oct 17, 2017 11:00:00 AM

If you’re relying on remnant patient samples to tell you how well your lab's bioinformatics pipeline can call clinically important variants, you might be missing more than you realize.

In our experience, the bioinformatics pipeline can be the weakest link in assay development for many labs. Just because a variant is sequenced correctly doesn’t always mean that it will be called. And false-positives are just as bad.

  • Sometimes it’s an issue of allele frequency. For example, we’ve seen cases where labs could detect certain mutations at 10% allele frequency, but as soon as the frequency dropped to 7%, they stopped detecting it.
  • Other cases are caused by the complexity of the variant. For example, even at low allele frequencies, a lab may pick up relatively easy-to-detect single-nucleotide variants (SNVs) but can have problems with insertion/deletion (INDEL) calling errors.

In both examples, the mutations aren’t missed because of sequencing or library preparation problems. As we’ve witnessed time and time again, when labs optimize their bioinformatics pipelines, they start picking up the low-frequency and difficult-to-detect variants again.

The catch is, you first have to know you’re missing something. In assay development, what you don’t know can seriously weaken your test.

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Topics: allele frequencies, next-generation sequencing, cancer profiling, bioinformatics


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