{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T19:44:14Z","timestamp":1792266254861,"version":"4.4.0"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":5,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,2]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>The 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We 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\u2009=\u20090.987 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>MAJEC 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag737","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T11:56:13Z","timestamp":1790855773000},"source":"Crossref","is-referenced-by-count":0,"title":["MAJEC: unified gene, isoform, and locus-level transposable element quantification from RNA-seq"],"prefix":"10.1093","volume":"42","author":[{"given":"Tian-Yeh","family":"Lim","sequence":"first","affiliation":[{"name":"Calico Life Sciences LLC , South San Francisco, CA 94080,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9902-443X","authenticated-orcid":false,"given":"Ari J","family":"Firestone","sequence":"additional","affiliation":[{"name":"Calico Life Sciences LLC , South San Francisco, CA 94080,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,5]]},"reference":[{"key":"2026101714574052500_btag737-B1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12943-016-0568-5","article-title":"SPAG6 and L1TD1 are transcriptionally regulated by DNA methylation in non-small cell lung cancers","volume":"16","author":"Altenberger","year":"2017","journal-title":"Mol Cancer"},{"key":"2026101714574052500_btag737-B2","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1093\/bioinformatics\/btu638","article-title":"HTSeq\u2014a Python 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