ArticleBioinformatics advances2026
isoespy: an integrated long-read transcriptome workflow for isoform resolution and visualization.
Article in Bioinformatics advances, 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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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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2 authors.
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Abstract
Summary: Long-read RNA-seq uncovers complex transcriptome diversity, opening new avenues for isoform-level expression analysis. Nevertheless, the functional diversity of individual isoforms is still poorly understood. We introduce isoespy, an analysis pipeline for integrating isoform structures, differential expression, and functional annotations from long-read RNA-seq data. The workflow integrates third-party open reading frame predictors, juxtaposes isoform expression levels with gene models, and visualizes positional and non-positional user-provided features. We applied isoespy to a transcriptome dataset of hepatocellular carcinoma, identifying differences in isoform usage and predicted protein function. isoespy facilitates the interpretation of transcriptomic complexity through integrated structural and functional visualization. Availability and implementation: Isoespy is freely available at https://github.com/kolikem/isoespy.
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Registered trials
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