Nanopore signal analysis enables detection of nucleotide modifications from native DNA and RNA sequencing, providing both accurate genetic/transcriptomic and epigenetic information without additional library preparation. Presently, only a limited set of modifications can be directly basecalled (e.g. 5-methylcytosine), while most others require exploratory methods that often begin with alignment of nanopore signal to a nucleotide reference. We present Uncalled4, a toolkit for nanopore signal alignment, analysis, and visualization. Uncalled4 features an efficient banded signal alignment algorithm, BAM signal alignment file format, statistics for comparing signal alignment methods, and a reproducible de novo training method for k-mer-based pore models, revealing potential errors in ONT's state-of-the-art DNA model. We apply Uncalled4 to RNA 6-methyladenine (m6A) detection in seven human cell lines, identifying 26% more modifications than Nanopolish using m6Anet, including in several genes where m6A has known implications in cancer. Uncalled4 is available open-source at github.com/skovaka/uncalled4.
Uncalled4 improves nanopore DNA and RNA modification detection via fast and accurate signal alignment.
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作者:Kovaka Sam, Hook Paul W, Jenike Katharine M, Shivakumar Vikram, Morina Luke B, Razaghi Roham, Timp Winston, Schatz Michael C
| 期刊: | bioRxiv | 影响因子: | 0.000 |
| 时间: | 2024 | 起止号: | 2024 Mar 10 |
| doi: | 10.1101/2024.03.05.583511 | ||
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