From days to hours: reporting clinically actionable variants from whole genome sequencing

Area of Science:

• Genomics and Bioinformatics
• Clinical Diagnostics

Background:

• Whole genome sequencing (WGS) adoption in clinical labs is increasing due to falling costs.
• Rapid reporting of WGS results is crucial for timely patient care, but data processing is a bottleneck.
• Current workflows spend significant time aligning non-clinically relevant genomic regions.

Purpose of the Study:

• To investigate a multi-step alignment algorithm to accelerate the reporting of clinically actionable variants from WGS data.
• To assess the accuracy of the proposed workflow compared to existing methods.

Main Methods:

• Developed and implemented an iterative workflow focusing on aligning reads and calling variants in clinically relevant genomic regions first.
• Compared variant calling accuracy against the OMNI SNP platform and a standard Novoalign/GATK workflow.
• Evaluated the acceleration in reporting clinically actionable variants.

Main Results:

• The multi-step alignment algorithm significantly accelerates the reporting of clinically actionable variants.
• The proposed workflow demonstrated no loss of accuracy compared to established genotyping platforms and standard WGS analysis pipelines.
• Prioritizing clinically relevant regions reduces overall data processing time.

Conclusions:

• This iterative alignment strategy offers a viable solution to expedite clinical variant reporting from whole genome sequencing.
• The method enhances the clinical utility of WGS by improving turnaround times without sacrificing diagnostic accuracy.
• Optimized bioinformatics workflows are essential for the broad clinical adoption of WGS technologies.