ArticleNucleic acids research2025
Accurate quantification of nascent and mature RNAs from single-cell and single-nucleus RNA-seq.
Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Integrating zero-inflation correction and transcriptional kinetics for single-cell transcriptomic analysis.PLoS computational biology · 2026Article
- Long-read sequencing transcriptome quantification with lr-kallisto.PLoS computational biology · 2025Article
- Biophysical constraints on mRNA decay rates shape macroevolutionary divergence in steady-state abundances.bioRxiv : the preprint server for biology · 2025Article
- Pseudoassembly of k-mers.bioRxiv : the preprint server for biology · 2025Article
- Efficient and accurate detection of viral sequences at single-cell resolution reveals putative novel viruses perturbing host gene expression.bioRxiv : the preprint server for biology · 2025Article
- Stochastic Modeling of Biophysical Responses to Perturbation.bioRxiv : the preprint server for biology · 2024Article
- Forseti: a mechanistic and predictive model of the splicing status of scRNA-seq reads.Bioinformatics (Oxford, England) · 2024Article
- The impact of package selection and versioning on single-cell RNA-seq analysis.bioRxiv : the preprint server for biology · 2024Article
- Molecularly stratified hypothalamic astrocytes are cellular foci for obesity.Research square · 2024Article
- Forseti: A mechanistic and predictive model of the splicing status of scRNA-seq reads.bioRxiv : the preprint server for biology · 2024Article
- kallisto, bustools, and kb-python for quantifying bulk, single-cell, and single-nucleus RNA-seq.bioRxiv : the preprint server for biology · 2024Article
- Biophysically Interpretable Inference of Cell Types from Multimodal Sequencing Data.bioRxiv : the preprint server for biology · 2023Article
- Understanding and evaluating ambiguity in single-cell and single-nucleus RNA-sequencing.bioRxiv : the preprint server for biology · 2023Article
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7 authors.
Funding
Abstract
In single-cell and single-nucleus RNA sequencing (RNA-seq), the coexistence of nascent (unprocessed) and mature (processed) messenger RNA (mRNA) poses challenges in accurate read mapping and the interpretation of count matrices. The traditional transcriptome reference, defining the "region of interest" in bulk RNA-seq, restricts its focus to mature mRNA transcripts. This restriction leads to two problems: reads originating outside of the "region of interest" are prone to mismapping within this region, and additionally, such external reads cannot be matched to specific transcript targets. Expanding the "region of interest" to encompass both nascent and mature mRNA transcript targets provides a more comprehensive framework for RNA-seq analysis. Here, we introduce the concept of distinguishing flanking k-mers (DFKs) to improve mapping of sequencing reads. We have developed an algorithm to identify DFKs, which serve as a sophisticated "background filter", enhancing the accuracy of mRNA quantification. This dual strategy of an expanded region of interest coupled with the use of DFKs enhances the precision in quantifying both mature and nascent mRNA molecules, as well as in delineating reads of ambiguous status.
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