Long-read sequencing technologies demonstrate high potential for de novo discovery of complex transcript isoforms, but high error rates pose a significant challenge. Existing error correction methods rely on clustering reads based on isoform-level alignment and cannot be efficiently scaled. We propose a new method, I-CONVEX, that performs fast, alignment-free isoform clustering with almost linear computational complexity, and leads to better consensus accuracy on simulated, synthetic, and real datasets.
CITATION STYLE
Baharlouei, S., Razaviyayn, M., Tseng, E., & Tse, D. (2023). I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads. In Communications in Computer and Information Science (Vol. 1753 CCIS, pp. 339–363). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-23633-4_23
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