Sequencing data for "Quantifying replication fidelity of unnatural base pairs using nanopore sequencing"
This project contains the nanopore sequencing datasets associated with the study "Quantifying replication fidelity of unnatural base pairs using nanopore sequencing." The datasets support the development and application of a nanopore sequencing-based approach for measuring the replication fidelity of unnatural base pairs (UBPs). Included are sequencing datasets used to train and test machine-learning classifiers for UBP detection, as well as PCR-amplified datasets used to quantify UBP replication fidelity. The data encompass three distinct UBP systems: B:S, P:Z, and Ds:Diol-Px. All sequencing data were generated using Oxford Nanopore Technologies (ONT) Flongle flow cells with R10.4.1 chemistry and basecalled using Dorado v0.8.0 with the dna_r10.4.1_e8.2_400bps_hac@v5.0.0 model and a minimum Q-score threshold of 5.