{
  "abstract": "LINE-1 RNA has emerged as a potential regulator of chromatin organization and gene expression, as well as a candidate readout of cellular and disease-associated states. Accurate measurement of LINE-1 transcript abundance is therefore important for evaluating its regulatory, biomarker, and potential therapeutic relevance. Measurement is challenging in short-read RNA sequencing because similar LINE-1 loci produce ambiguous, multi-mapping reads and LINE-1-associated signal can arise from passive as well as autonomous transcription. We developed the Transformers Analysis Pipeline (TrAP), an alignment-free ALBERT-based workflow that classifies short RNA-seq reads as L1HS, L1PA, or non-LINE-1 before abundance estimation, converting overlapping k-mers to integer tokens and integrating predictions with Salmon- or expectation–maximization-based quantification. TrAP was evaluated using synthetic LINE-1 insertion datasets and HEK293 short-read RNA-seq benchmarked against 5′ rapid amplification of cDNA end (5′RACE) long-read measurements. AlbertSalmon agreed most closely with the synthetic insertion levels, ranking first in all insertion levels and deletion-probability strata. Agreement with the 5′RACE reference was also highest, although the locus-level gain there was only incremental. High-attribution k-mers were modestly over-represented within functional ORF2 coding regions rather than being uniformly distributed across LINE-1. These findings support TrAP as a transformer-assisted framework for improving LINE-1 quantification in short-read RNA-seq datasets, thereby supporting future regulatory and biomarker studies.",
  "abstract_shown": true,
  "affiliations": [
    "Center for Genomic and Precision Medicine, Texas A&M Institute of Biosciences and Technology, Texas Medical Center, Houston, TX 77030, USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Andres D. Chamorro-Parejo",
      "orcid": "0000-0002-1716-9027"
    },
    {
      "affs": [
        0
      ],
      "name": "Kenneth S. Ramos",
      "orcid": "0000-0002-0692-4066"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/0gyzbb761n66n.bib",
  "cited_by": 0,
  "doi": "10.3390/ijms27219762",
  "fulltext_url": null,
  "id": "0gyzbb761n66n",
  "issns": [
    "1422-0067"
  ],
  "landing_url": "https://www.mdpi.com/1422-0067/27/21/9762",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/0gyzbb761n66n.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:54Z",
      "native_id": "10.3390/ijms27219762",
      "source": "crossref",
      "url": "https://www.mdpi.com/1422-0067/27/21/9762"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "issn:1422-0067",
      "subfield": "general"
    }
  ],
  "title": "A Transformers Analysis Pipeline (TrAP) to Evaluate LINE-1 RNA Sequence Content",
  "title_text": "A Transformers Analysis Pipeline (TrAP) to Evaluate LINE-1 RNA Sequence Content",
  "type": "peer-reviewed",
  "updated_at": "2026-11-01T00:20:52Z",
  "url": "https://research.draconitic.com/paper/0gyzbb761n66n",
  "venue": "International Journal of Molecular Sciences",
  "versions": []
}