Abdolrahman Khezri, Sverre Branders, Anurag Basavaraj Bellankimath, Jawad Ali, Crystal Chapagain, Fatemeh Asadi, Manfred G Grabherr, Rafi Ahmad
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MysteryMaster: scraping the bottom of the barrel of barcoded Oxford nanopore reads.
Background: The high error rate associated with Oxford Nanopore sequencing technology adversely affects demultiplexing. To improve demultiplexing and reduce unclassified reads from nanopore sequencing data, we developed MysteryMaster, a demultiplexer that utilizes the optimal sequence aligner, Cola.
Results: When compared to Oxford Nanopore´s Dorado and Guppy demultiplexing tools across three datasets of 37 diverse samples with established ground truth, we found that MysteryMaster accurately identifies a similar or greater percentage of reads among the different basecalling models: Fast, HAC, and SUP. MysteryMaster performs slightly better than the other tools on data that was basecalled using the Fast basecalled model, while its performance in HAC and SUP data is similar to Dorado's. MysteryMaster has a false positive rate of just 0.41% with default settings.
Conclusions: While MysteryMaster can function as a standalone demultiplexer tool, the sequential application of Dorado and MysteryMaster produced the best overall performance.
期刊介绍：
BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology.
BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.
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