CRANE: Correcting Errors in Raw Nanopore Signals Using Hidden Markov Models
Nanopore sequencing can read substantially longer sequences of nucleic acid molecules, called reads, than other sequencing methods, which has led to advances in genomic analysis such as the gapless human genome assembly. By analyzing the raw electrical signal reads that nanopore sequencing generates from molecules, existing works can map these reads without translating them into DNA characters (i.e., basecalling), allowing for quick and efficient analysis of sequencing data. However, raw signals often contain errors due to noise and processing errors, which limits the overall accuracy of raw signal analysis. Our goal in this work is to detect and correct errors in raw signals to improve t...
| Authors | Simon Ambrozak, Ulysse McConnell, Bhargav Srinivasan et al. |
|---|---|
| Primary category | q-bio.GN |
| Published | 20 March 2026 |
| Last updated at source | 20 May 2026 |
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