{
  "abstract": "Motivation\n\nThe study of transposable elements (TEs) has become increasingly central to fields such as cancer biology, immunology, and aging. Accurately quantifying disease- or laboratory-mediated perturbations in these elements is critical to support this expanding research, yet current RNA-seq pipelines struggle with the pervasive overlap between TEs and protein-coding genes. Existing tools either aggregate to the subfamily level with no locus resolution (TEtranscripts), or provide locus-level quantification without modeling gene overlap (Telescope), with the latter attributing over 40% of TE signal to the 1.1% of loci that overlap gene exons.Results\n\nWe present Momentum Accelerated Junction Enhanced Counting (MAJEC), a unified Expectation-Maximization (EM) framework that jointly quantifies genes, transcript isoforms, and individual TE loci from BAM alignments in a single pass. Splice junction evidence informs transcript-level priors, enabling MAJEC to probabilistically distinguish genic from TE-derived reads. This approach was independently validated against Salmon and RSEM on isoform quantification benchmarks. The joint feature space reduces exon-overlap contamination of locus-level TE estimates from 43% of total signal (Telescope) to 5% (MAJEC), while preserving subfamily-level accuracy (differential expression r = 0.987 versus TEtranscripts). Using paired biological vignettes, we demonstrate that MAJEC correctly resolves both the false TE reactivation artifacts endemic to TE-only models, and the false gene upregulation artifacts that occur when heuristic rules misassign genuine intragenic TE transcription. MAJEC simultaneously produces the isoform and locus-level resolution that TEtranscripts lacks, with greater accuracy than Telescope, and runs faster than either.Availability and implementation\n\nMAJEC is available at https://github.com/calico/majec and via PyPI/Bioconda; analysis code and data are deposited at https://doi.org/10.5281/zenodo.19224157.",
  "abstract_shown": true,
  "affiliations": [
    "Calico Life Sciences LLC, South San Francisco, CA 94080, United States."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Tian-Yeh Lim"
    },
    {
      "affs": [
        0
      ],
      "name": "Ari J Firestone",
      "orcid": "0000-0001-9902-443X"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3pknmq4vnshbn.bib",
  "cited_by": 0,
  "doi": "10.1093/bioinformatics/btag737",
  "fulltext_url": "https://europepmc.org/articles/PMC13676384",
  "id": "3pknmq4vnshbn",
  "issns": [
    "1367-4803",
    "1367-4811"
  ],
  "landing_url": "https://europepmc.org/article/MED/42834519",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1312|Genomics and Phylogenetic Studies"
    ]
  ],
  "openalex": "W7154224357",
  "pdf_url": "https://europepmc.org/articles/PMC13676384?pdf=render",
  "pmcid": "PMC13676384",
  "pmid": "42834519",
  "published": "2026-10-01",
  "publisher": "Oxford University Press (OUP)",
  "ris": "https://research.draconitic.com/paper/3pknmq4vnshbn.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:10Z",
      "native_id": "MED:42834519",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42834519"
    },
    {
      "first_seen": "2026-10-30T12:19:38Z",
      "native_id": "10.1093/bioinformatics/btag737",
      "source": "crossref",
      "url": "https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btag737/8866687"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "openalex:1312|Genomics and Phylogenetic Studies",
      "subfield": "molecular-biology"
    }
  ],
  "title": "MAJEC: unified gene, isoform, and locus-level transposable element quantification from RNA-seq.",
  "title_text": "MAJEC: unified gene, isoform, and locus-level transposable element quantification from RNA-seq.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:38Z",
  "url": "https://research.draconitic.com/paper/3pknmq4vnshbn",
  "venue": "Bioinformatics (Oxford, England)",
  "versions": []
}