Clinical Assessment of Next-Generation Sequencing Probe Reproducibility in Short-Read Sequencing (ClinRay) Using...

Area of Science:

• Genomics
• Bioinformatics
• Clinical Diagnostics

Background:

• Short-read next-generation sequencing (NGS) is crucial for clinical diagnosis but struggles with variant detection in complex genomic regions.
• These regions, including segmental duplications and repeat sequences, impact variant detection reproducibility.
• Current validation methods are costly and time-consuming, delaying clinical results.

Purpose of the Study:

• To develop a novel bioinformatics method, ClinRay, to predict variant detection reproducibility in difficult-to-sequence genomic regions.
• To address the limitations of short-read NGS in complex genomic areas.
• To improve the accuracy and efficiency of variant detection for clinical applications.

Main Methods:

• ClinRay utilizes a "digital twin" approach to synthetically enhance data for regions with suspected poor reproducibility.
• The model was trained using alignment data from eight replicates of the Genome in a Bottle HG002 cell line.
• Publicly available genomic context annotation resources were integrated into the model development.

Main Results:

• ClinRay achieved an area under the receiver-operating characteristic curve (AUC) of 0.89 (95% CI, 0.88-0.90) on test data.
• The model demonstrated strong performance on an independent validation dataset with an AUC of 0.85 (95% CI, 0.84-0.86).
• ClinRay effectively predicts the reproducibility of variants detected by short-read NGS probes.

Conclusions:

• ClinRay offers a generalizable bioinformatics solution for improving variant detection reproducibility in challenging genomic regions.
• The method has the potential to reduce costs and turnaround times in clinical laboratories.
• ClinRay enhances the reliability of short-read NGS for clinical variant interpretation.