ArticleBioinformatics (Oxford, England)2026
isoSeQL: comparing long-read isoforms across multiple datasets.
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 1 paper.
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Who cites it
1 citing paper in PubMed.
- RNA isoform diversity, splicing variants and switching in single cells of the Alzheimer's disease brain.Communications biology · 2026Article
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Authors and funding
2 authors.
Funding
Abstract
motivationLong-read sequencing has made RNA isoform detection and characterization more accessible. While several bioinformatics tools have been developed to examine the data generated by these approaches, a major challenge in the field has been comparing isoform profiles across several samples.
resultsWe developed isoSeQL, a tool for compiling long-read transcriptomic data, identifying common and unique isoforms across multiple samples, and extracting and visualizing various metrics. isoSeQL will augment approaches that utilize long-read sequencing to discover novel isoforms and to examine how isoforms vary across different experimental and biological conditions and cell types. We demonstrate how to use isoSeQL with publicly available datasets. AVAILABILITY AND IMPLEMENTATION: isoSeQL is available on Github: https://github.com/christine-liu/isoSeQL and Zenodo:https://doi.org/10.5281/zenodo.15717809.
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Registered trials
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