Abstract
Duplex sequencing is currently the most reliable method to identify ultra-low frequency DNA variants by grouping sequence reads derived from the same DNA molecule into families with information on the forward and reverse strand. However, only a small proportion of reads are assembled into duplex consensus sequences, and reads with potentially valuable information are discarded at different steps of the bioinformatics pipeline, especially reads without a family. We developed a bioinformatics tool-set that analyses the tag and family composition with the purpose to understand data loss and implement modifications to maximize the data included in variant calling. In addition, we also developed a tool called Variant Analyzer that re-examines variant calls from raw reads and provides different summary data that categorizes the confidence level of a variant call by a tier-based system. We demonstrate that this tool identifies false positive variants with support from the tier-based classification. Furthermore, with this tool we can include reads without a family and check the reliability of the call, which increases substantially the sequencing depth for variant calling, a particular important advantage for low-input samples or low-coverage regions.
Footnotes
Abbreviations
- AF
- allele frequency
- SSCS
- Single Strand Consensus Sequence
- DCS
- Duplex Consensus Sequence
- DS
- Duplex Sequencing
- PCR
- Polymerase Chain Reaction
- FS
- family size
- RL
- read length
- TD
- tag distance
- PE
- paired-end
- CA
- Chimera Analysis