ERASE-Seq: Leveraging replicate measurements to enhance ultralow frequency variant detection in NGS data

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Accurate detection of ultralow allele frequency variants is crucial for research and medical applications, especially in liquid biopsies for cancer monitoring.
• Next-generation sequencing (NGS) with molecular barcoding shows promise but requires enhanced sensitivity and specificity for early cancer detection.

Purpose of the Study:

• To present analytical validation data for ERASE-Seq, a novel method for sensitive and accurate detection of ultralow frequency DNA variants in NGS data.
• To address the need for improved sensitivity and specificity in detecting cancer mutations from circulating DNA.

Main Methods:

• ERASE-Seq utilizes a statistical framework incorporating technical replicates and background error modeling.
• The method was analytically validated using spiked human DNA mixtures with clinically relevant input quantities.

Main Results:

• ERASE-Seq achieved a 10 to 100-fold reduction in false positive rates compared to existing molecular barcoding methods.
• The method demonstrated >90% sensitivity for detecting single nucleotide variants (SNVs) and indels between 0.05% and 1% allele frequency.
• A false positive rate below 0.1 calls per 10,000 possible variants was achieved.

Conclusions:

• ERASE-Seq offers significant performance improvements for detecting ultralow frequency DNA variants in NGS data.
• The method enhances accuracy and sensitivity without requiring changes to molecular reagents, making it broadly applicable.