Sign in
BioinformaticsbioRxiv
Preprint

I-CONVEX: Fast and Accurate de Novo Transcriptome Recovery from Long Reads

Sina BaharloueiiD, Meisam RazaviyayniD, Elizabeth TsengiD, David N. C. TseiD

Abstract

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.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISSahlin '20Petri '25Marchet '18Broséus '20Westrin '22Lima '19
70% semantic matchBioinformatics
Kristoffer Sahlin, Paul Medvedev·Journal of Computational Biology·Mar 17, 2020· 98 citations