ArticleBioinformatics (Oxford, England)2025
Oarfish: enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification.
Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed.
- Bramble: projection of spliced genomic alignments into transcriptomic space for improved transcript quantification.bioRxiv : the preprint server for biology · 2026Article
- The promise of long-read RNA-seq: reducing bias in analyses of allele imbalance.NAR genomics and bioinformatics · 2026Article
- Benchmarking RNA-seq with the Quartet and MAQC reference materials to establish best practices for accurate alternative splicing analysis.Nature communications · 2026Article
- Beyond the gene: isoform diversity as a key contributor to human brain disorders.Current opinion in genetics & development · 2026Review
- Leviathan: A fast, memory-efficient, and scalable taxonomic and pathway profiler for (pan)genome-resolved metagenomics and metatranscriptomics.bioRxiv : the preprint server for biology · 2026Article
- Gene- and Isoform-Level Responses to Extreme Acidic pH Stress in an Emerging Marine Invertebrate Model OrganismAntioxidants (Basel, Switzerland) · 2026Article
- Pangenome-based human genome analysis improves trait association and genomic prediction.bioRxiv : the preprint server for biology · 2026Article
- Augmenting transcriptome annotations through the lens of splicing evolution.Genome research · 2026Article
- Influence ofGenome research · 2026Article
- Hybrid untargeted short-read and targeted long-read RNA sequencing facilitates genotype-phenotype associations at single-cell resolution.Genome biology · 2026Article
- An rRNA-depleted full-length transcriptome strategy using nanopore sequencing for identification of novel lncRNA isoforms.Communications biology · 2026Article
- Aberrant CD4bioRxiv : the preprint server for biology · 2026Article
- Efficient reconstruction of full-length RNA isoforms using ISAtools and large-scale PacBio circular consensus sequencing data.Briefings in bioinformatics · 2026Article
- SNP calling, haplotype phasing and allele-specific analysis with long RNA-seq reads.Nature methods · 2026Article
- Population-scale interpretation of RNA isoform diversity enabled by Isopedia.bioRxiv : the preprint server for biology · 2026Article
- BenchDrop-seq: a microfluidics-free platform for benchtop single-cell long-read RNA sequencing.bioRxiv : the preprint server for biology · 2026Article
- A systematic benchmark of high-accuracy PacBio long-read RNA sequencing for transcript-level quantification.Genome biology · 2026Article
- A comprehensive evaluation of long-read de novo transcriptome assembly.Genome biology · 2026Article
- Accurate strand-specific long-read transcript isoform discovery and quantification at bulk, single-cell, and single-nucleus resolution.bioRxiv : the preprint server for biology · 2026Article
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Abstract
motivationLong-read sequencing technology is becoming an increasingly indispensable tool in genomic and transcriptomic analysis. In transcriptomics in particular, long reads offer the possibility of sequencing full-length isoforms, which can vastly simplify the identification of novel transcripts and transcript quantification. However, despite this promise, the focus of much long-read method development to date has been on transcript identification, with comparatively little attention paid to quantification. Yet, due to differences in the underlying protocols and technologies, lower throughput (i.e. fewer reads sequenced per sample compared to short-read technologies), as well as technical artifacts, long-read quantification remains a challenge, motivating the continued development and assessment of quantification methods tailored to this increasingly prevalent type of data.
resultsWe introduce a new method and corresponding user-friendly software tool for long-read transcript quantification called oarfish. Our model incorporates a novel coverage score, which affects the conditional probability of fragment assignment in the underlying probabilistic model. We demonstrate, in both simulated and experimental data, that by accounting for this coverage information, oarfish is able to produce more accurate quantification estimates than existing long-read quantification tools. AVAILABILITY AND IMPLEMENTATION: oarfish is implemented in the Rust programming language and is made available as free and open-source software under the BSD 3-clause license. The source code is available at https://www.github.com/COMBINE-lab/oarfish.
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