A comprehensive evaluation of long-read de novo transcriptome assembly
Our results confirm that long reads generate longer assembled transcripts than short-reads for reference-free analysis, though limitations remain compared to reference-guided approaches, and suggest scope for improved accuracy and reduced redundancy. Of the de novo pipelines, RNA-Bloom2, coupled with Corset for transcript clustering, was the best performing in terms of both accuracy and computational efficiency. Our findings offer guidance when selecting the most effective strategy for long-read differential expression analysis, when a high-quality reference genome is unavailable.
Authors
- Mathew G. Lewsey (ORCID: https://orcid.org/0000-0002-2631-4337)
- N. Davidson
- Quentin Gouil
- Matthew E. Ritchie
- James Lancaster
- Feng Yan
- Pedro L. Baldoni
Institutions
- Australian Research Council (AU)
- The University of Melbourne (AU)
- Walter and Eliza Hall Institute of Medical Research (AU)
- La Trobe University (AU)
- Melbourne Health (AU)
- Olivia Newton-John Cancer Wellness & Research Centre (AU)
Publication Details
- Journal
- Genome biology
- Published
- 2026-02-18
- DOI
- https://doi.org/10.1186/s13059-026-04001-5
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00