Isoformic: a workflow for transcript-level RNA-seq interpretation. Academic Article uri icon

Overview

abstract

  • Transcriptome analysis is one of the bases of modern biology, yet it is typically performed at the gene level, ignoring the complexity of alternative splicing and differential transcription initiation/termination events. Over 95% of mammalian genes produce multiple transcripts, yet most RNA-seq analyses rely on short-read data, for which transcript-level interpretation remains challenging. Current tools suffer from low accuracy, inconsistency with annotations, and lack quick solutions for downstream biological interpretation. Here, we present Isoformic, a customizable R pipeline for transcript-level analysis of short-read RNA-seq data, available on GitHub. Isoformic processes differential expression results to detect genes with transcript-level changes, visualize exon-intron structures, and perform functional enrichment stratified by transcript type. Validated on diverse datasets, including preeclampsia, SARS-CoV-2 infection, and murine anxiety models, Isoformic reveals biologically relevant transcript variants and their possible phenotypic associations. Compatible with GENCODE reference transcriptome, Isoformic enhances the resolution of RNA-seq studies, enabling researchers to uncover the regulatory roles of alternative transcription events.

publication date

  • December 3, 2025

Research

keywords

  • Gene Expression Profiling
  • RNA-Seq
  • Sequence Analysis, RNA
  • Software
  • Transcriptome

Identity

PubMed Central ID

  • PMC12673842

Digital Object Identifier (DOI)

  • 10.1093/nargab/lqaf176

PubMed ID

  • 41347231

Additional Document Info

volume

  • 7

issue

  • 4