ArticleBioinformatics (Oxford, England)2026
GeneExt: a gene model extension tool for enhanced single-cell RNA-seq analysis.
Article in Bioinformatics (Oxford, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Diversity and evolution of chromatin regulatory states across eukaryotes.Nature genetics · 2026Article
- Experimental and computational methods for allelic imbalance analysis from single-nucleus RNA-seq data.Genome biology · 2026Article
- The evolution of gene regulation in mammalian cerebellum development.Science (New York, N.Y.) · 2026Article
- Spatially resolved gene expression analysis illuminates location-specific functions in the reef-building coral Pocillopora acuta.PloS one · 2026Article
- Co-option of transcription factors drives evolution of quantitative disease resistance against a necrotrophic pathogen.The Plant cell · 2025Article
- Establishing single cell RNA transcriptomics: a brief guide.Frontiers in zoology · 2025Review
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Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
motivationIncomplete gene models negatively impact single-cell gene expression quantification. This is particularly true in non-model species where often gene 3' ends are inaccurately annotated, while most scRNA-seq methods only capture the 3' transcript region. This results in many genes being incorrectly quantified or not detected.
resultsGeneExt leverages scRNA-seq data to refine gene annotations. We exemplify GeneExt usage and its impact on the gene expression quantification of eight non-model organism single-cell atlases. By extending and homogenizing gene annotations, our tool will help improve biological interpretation and cross-species comparisons of cell type expression atlases. AVAILABILITY: GeneExt is available at https://github.com/sebepedroslab/GeneExt (DOI: https://doi.org/10.5281/zenodo.18712940) under a GNU General Public license, together with test data and usage instructions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.