ArticleGenome biology2025
Enhancing transcriptome expression quantification through accurate assignment of long RNA sequencing reads with TranSigner.
Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 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
- Long-Read Sequencing Reveals RNA Splicing Complexity in Human Diseases.Computational and structural biotechnology journal · 2026Review
- Long-read sequencing transcriptome quantification with lr-kallisto.PLoS computational biology · 2025Article
- Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.bioRxiv : the preprint server for biology · 2025Article
- Oarfish: enhanced probabilistic modeling leads to improved accuracy in long read transcriptome quantification.Bioinformatics (Oxford, England) · 2025Article
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Abstract
Long-read RNA sequencing captures transcripts at full lengths, but existing methods for transcriptome profiling using long-read data often produce inconsistent transcript identification and quantification results. Here, we introduce TranSigner, a tool designed to provide read-level support for transcripts in a given transcriptome. TranSigner consists of three modules: read alignment to transcripts, computation of read-to-transcript compatibility scores, and a guided expectation-maximization algorithm to assign reads to transcripts and estimate their abundances. Using simulated and experimental data from three well-studied organisms-Homo sapiens, Arabidopsis thaliana, and Mus musculus-we show that TranSigner achieves accurate read assignments and abundance estimates.
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