{
  "abstract": "The advancement of long-read RNA sequencing technologies leads to a bright future for transcriptome analysis. Reconstructing alternative isoforms from long-read RNA data is crucial in transcriptomic studies and poses computational challenges. In this research, we study the heterogeneity of current long reads RNA-seq data, and categorize the sequencing data into two types according to the fraction of the alternative splicing events appeared in the extracted reliably supported sub-path of the splicing graph. Leveraging the heterogeneity, we develop TransGram, an algorithm to reconstruct transcriptome from long RNA-seq reads, which employs the traditional assemble strategy to reconstruct the transcript-representing paths within the splicing graph, and incorporates a machine-learning-based model trained on splice graph-derived features to eliminate false positive transcripts. TransGram supports both annotation-free and annotation-guided modes. Comprehensive evaluations across multiple datasets and conditions demonstrate that TransGram consistently outperforms widely used tools StringTie2, IsoQuant, Bambu, and ESPRESSO, in terms of precision and recall.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Zitong Ren",
      "orcid": "0009-0000-9432-5866"
    },
    {
      "name": "Junhai Qi"
    },
    {
      "name": "Renmin Han"
    },
    {
      "name": "Shengkai Guo",
      "orcid": "0009-0007-7480-051X"
    },
    {
      "name": "Jiahao Li",
      "orcid": "0009-0003-8850-7833"
    },
    {
      "name": "Mingyu Liu"
    },
    {
      "name": "Guojun Li",
      "orcid": "0000-0003-1581-5897"
    },
    {
      "name": "Ting Yu",
      "orcid": "0000-0002-0073-9644"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1fz6ym1ydvdcn.bib",
  "cited_by": 0,
  "doi": "10.1038/s41467-026-78013-x",
  "fulltext_url": "https://europepmc.org/articles/PMC13728183",
  "id": "1fz6ym1ydvdcn",
  "issns": [
    "2041-1723"
  ],
  "landing_url": "https://www.nature.com/articles/s41467-026-78013-x",
  "language": "eng",
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0",
  "metadata_licence": null,
  "native_subjects": [
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      "openalex",
      "1312|Genomics and Phylogenetic Studies"
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  "pdf_url": "https://www.nature.com/articles/s41467-026-78013-x_reference.pdf",
  "pmcid": "PMC13728183",
  "pmid": "42971978",
  "published": "2026-10-05",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/1fz6ym1ydvdcn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:38Z",
      "native_id": "10.1038/s41467-026-78013-x",
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      "url": "https://www.nature.com/articles/s41467-026-78013-x"
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      "url": "https://doi.org/10.1038/s41467-026-78013-x"
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  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Genomics and Phylogenetic Studies",
      "subfield": "molecular-biology"
    }
  ],
  "title": "TransGram for heterogeneity-aware transcriptome reconstruction from long read RNA-Seq data",
  "title_text": "TransGram for heterogeneity-aware transcriptome reconstruction from long read RNA-Seq data",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T12:21:13Z",
  "url": "https://research.draconitic.com/paper/1fz6ym1ydvdcn",
  "venue": "Nature Communications",
  "versions": []
}