bioRxivGenomicsPreprint
Characterizing and addressing error modes to improve sequencing accuracy
Semyon KruglyakiD, Andrew Altomare, Mark R. Ambroso, Vivian T. DieniD, Bryan R. LajoieiD, Kelly N. Wiseman, Shawn LevyiD, Matthew William Kellinger
- Citations
- 5
Abstract
The accuracy of a sequencing platform has traditionally been measured by the %Q30, or percentage of data exceeding a basecall accuracy of 99.9%. Improvements to accuracy beyond Q30 may be beneficial for certain applications such as the identification of low frequency alleles or the improvement of reference genomes. Here we demonstrate how we achieved over 70% Q50 (99.999% accuracy) data on the AVITI sequencer. This level of accuracy required us to not only improve sequencing quality but also to mitigate library preparation errors and analysis artifacts.
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