Sequins WGS Clinical Control Set

Maximize insights from every sample with Sequins™ internal standards.

Sequins WGS Clinical Control Set v1.0 is based on the ACMG Secondary Findings list, covering 80 genes and 96 conditions. This control set represents a range of variant classes, enabling robust assessment of variant detection, coverage and analytical performance across clinically important genes.

Standardization within and between samples, users, equipment and locations

The use of Sequins controls for standardization mitigates the heterogeneity of samples to enable unprecedented interoperability.

Workflow Monitoring and Optimization

Sequins are subjected to the same technical influences and errors as the samples they are combined with, enabling the evaluation of workflow performance.

Enhanced clinical insights

Sequins are uniquely designed to represent variants across a range of classes in clinically important genes, enhancing the ability to confidently and reliably call variants.

Most Comprehensive WGS Clinical Control Set

Broad Coverage: Sequins representing 80 of the 84 clinically actionable ACMG Secondary Findings genes across cancer, cardiovascular, metabolic, and rare diseases.

Flexible and Compatible: Available as a standalone kit or in combination with the WGS Core Control Set for an integrated control system.

Comprehensive Variant Representation: Covers pathogenic /likely pathogenic, VUS and benign/likely benign variants in ACMG-listed secondary findings genes, enabling robust benchmarking of variant detection and reporting pipelines.

Gene list

wgs-clinic-gen-list

WGS Clinical Control Set v1.0 Performance

To assess performance of Sequins relative to native human genomic DNA (hgDNA), we compared read coverage across matched Sequins target regions. Sequins from the WGS Clinical Control Set v1.0 demonstrated strong concordance with hgDNA, and this relationship was preserved when combined with the WGS Core Control Set. These results confirm that Sequins recapitulate native sequence behaviour and can be integrated across control modules without compromising coverage.

Mean coverage of Sequins and hgDNA at the same location. (A) Reads mapped to the Sequins WGS Clinical Control Set v1.0 strongly correlated with the same regions of hgDNA (slope 0.89, R² = 0.83). (B) This correlation was maintained when combined with the WGS Core Control Set (slope 1.00, R² = 0.82), confirming compatibility without loss of performance.

Variant calling across the full genome of NA12878 showed precision and sensitivity above 99% in all conditions. Importantly, combining the WGS Clinical Control Set v1.0 with the WGS Core Control Set did not alter the accuracy of hgDNA variant calls. The observed differences were within the expected background noise of large-scale variant calling pipelines.

Sample	TP	FP	FN	Precision	Sensitivity	F-measure
NA12878 + WGS Clinical Control Set v1.0	3,682,018	28,890	18,083	0.9922	0.9951	0.9937
NA12878 + WGS Clinical Control Set v1.0 + WGS Core Control Set	3,682,079	28,849	18,009	0.9922	0.9951	0.9937

TP – true positive, FP – false positive, FN – false negative

Within the Sequins target regions, variant calling performance was near-perfect. Precision reached 100%, sensitivity exceeded 99.7%, and the only false negative was an expected structural variant not detectable by the germline variant caller used. Results were identical when combined with the WGS Core Control Set.

Sample	TP	FP	FN*	Precision	Sensitivity	F-measure
NA12878 + WGS Clinical Control Set v1.0	385	0	1	1.0000	0.9974	0.9987
NA12878 + WGS Clinical Control Set v1.0 + WGS Core Control Set	385	0	1	1.0000	0.9974	0.9987

TP – true positive, FP – false positive, FN – false negative
*The single false negative was expected due to limitation of the variant caller for structural variant

Plug & Play Simplicity

Sequins are simply ‘spiked-in’ to a sample prior to library preparation and together, progressed through a workflow. Sequins controls can then be distinguished from the native sample in the output library by their synthetic sequence enabling normalization and comparison between samples, runs, laboratories, chemistries, and sequencers.