Long-read sequencing transcriptome quantification with lr-kallisto
RNA abundance quantification has become routine and affordable thanks to high-throughput "short-read" technologies that provide accurate molecule counts at the gene level. Similarly accurate and affordable quantification of definitive full-length, transcript isoforms has remained a stubborn challenge, despite its obvious biological significance across a wide range of problems. "Long-read" sequencing platforms now produce data-types that can, in principle, drive routine definitive isoform quantification. However some particulars of contemporary long-read datatypes, together with isoform complexity and genetic variation, present bioinformatic challenges. We show here, using ONT data, that fast and accurate quantification of long-read data is possible and that it is improved by exome capture. To perform quantifications we developed lr-kallisto, which adapts the kallisto bulk and single-cell RNA-seq quantification methods for long-read technologies.
Authors
- Elisabeth Rebboah (ORCID: https://orcid.org/0000-0003-2273-0189)
- Páll Melsted (ORCID: https://orcid.org/0000-0002-8418-6724)
- Lior Pachter (ORCID: https://orcid.org/0000-0002-9164-6231)
- Diane Trout (ORCID: https://orcid.org/0000-0002-4928-5532)
- Ghassan Filimban (ORCID: https://orcid.org/0000-0002-2612-2554)
- A. Sina Booeshaghi (ORCID: https://orcid.org/0000-0002-6442-4502)
- Heidi Yahan Liang (ORCID: https://orcid.org/0000-0002-6190-9723)
- Rebekah K. Loving (ORCID: https://orcid.org/0000-0001-8725-0376)
- Shimako Kawauchi (ORCID: https://orcid.org/0000-0002-8577-4763)
- Jasmine Sakr (ORCID: https://orcid.org/0000-0002-4470-3192)
- B Wold (ORCID: https://orcid.org/0000-0003-3235-8130)
- Delaney K. Sullivan (ORCID: https://orcid.org/0000-0002-8359-6705)
- Conrad Oakes (ORCID: https://orcid.org/0000-0002-8936-055X)
- Fairlie Reese (ORCID: https://orcid.org/0000-0002-9240-0102)
- Narges Rezaie (ORCID: https://orcid.org/0000-0001-9326-9954)
- A Mortazavi (ORCID: https://orcid.org/0000-0002-4259-6362)
- Grant R. MacGregor (ORCID: https://orcid.org/0000-0001-7598-9501)
- Brian A. Williams (ORCID: https://orcid.org/0000-0003-3253-611X)
Institutions
- California Institute of Technology (US)
- deCODE Genetics (Iceland) (IS)
- University of California, Los Angeles (US)
- University of Iceland (IS)
- University of California, Irvine (US)
- University of California, Berkeley (US)
Publication Details
- Journal
- PLoS Computational Biology
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1371/journal.pcbi.1013692
- Citations
- 4
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 3.22