True measure of control

The Future of Genomics Data Quality

The Future of Genomics Data Quality
The Future of Genomics Data Quality
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Sequins™ are synthetic nucleic acid controls that directly mirror naturally occurring sequences

Our innovative design enables representation of almost any genomic feature, in any organism with a reference genome. Sequins retain the same nucleotide composition as the natural sequence and enable accurate representation of genomic complexity without compromising integrity of samples and results.

Sequins Provide a True Measure of Control

Because Sequins retain the same nucleotide composition as the natural sequence, they enable accurate representation of genomic complexity without compromising integrity of the sample and results.

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01
Improve Genomics Performance

Improve Genomics Performance

02
Reduce Error

Reduce Error

03
Increase DX Yield

Increase DX Yield

04
Normalize Data

Normalize Data

05
Unlock Longitudinal Insight

Unlock Longitudinal Insight

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What customers are saying about Sequins™

In clinical WGS, parallel control samples have always been an expensive compromise—they consume resources but add little clarity about how individual samples are performing. At best, they tell you that the sequencer ran, not whether each patient sample met your quality bar. By adopting Sequins spike-in controls, we can measure library prep, sequencing, and variant calling performance within each sample itself. This elevates QC from a perfunctory check into a robust, sample-specific assurance of sensitivity and accuracy.
Francisco M. De La Vega, D.Sc.
Former CTO, Galatea Bio Inc. and Adjunct Professor, Stanford University
Sequins was straightforward to implement in the wet lab and, importantly, allowed us to obtain absolute quantification — something we couldn't achieve when only measuring relative abundances. We chose Sequins after seeing a colleague's successful work, and the Metagenomics Core Control Set delivered exactly what we needed.
Alex Song
PhD student, University of Michigan
Sequins gave us the confidence to accurately quantify viruses in wastewater samples by distinguishing true biological signals from sequencing biases. Their ease of use and robust design made them an invaluable tool for improving accuracy and reliability in our metagenomics research.
Kathryn Langenfeld
Graduate Student Researcher & Postdoctoral Scholar, University of Michigan

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