{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T10:30:20Z","timestamp":1782210620138,"version":"3.54.5"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T00:00:00Z","timestamp":1738540800000},"content-version":"vor","delay-in-days":73,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Science and Technology Major Project of China","award":["2023ZD0502401"],"award-info":[{"award-number":["2023ZD0502401"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,11,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The accurate estimation of cell type proportions in tissues is crucial for various downstream analyses. With the increasing availability of single-cell sequencing data, numerous deconvolution methods that use single-cell RNA sequencing data as a reference have been developed. However, a unified understanding of how these deconvolution approaches perform in practical applications is still lacking. To address this, we systematically assessed the accuracy and robustness of nine deconvolution methods that use single-cell RNA sequencing data as a reference, evaluating them on real bulk data with cell proportions verified through flow cytometry, as well as simulated bulk data generated from five single-cell RNA sequencing datasets. Our study highlights the importance of several factors\u2014including reference dataset construction strategies, dataset size, cell type subdivision, and cell type inconsistency\u2014on the accuracy and robustness of deconvolution results. We also propose a set of recommended guidelines for software users in diverse scenarios.<\/jats:p>","DOI":"10.1093\/bib\/bbaf031","type":"journal-article","created":{"date-parts":[[2025,2,3]],"date-time":"2025-02-03T16:48:27Z","timestamp":1738601307000},"source":"Crossref","is-referenced-by-count":11,"title":["Cell-type deconvolution for bulk RNA-seq data using single-cell reference: a comparative analysis and recommendation guideline"],"prefix":"10.1093","volume":"26","author":[{"given":"Xintian","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Molecular Virology and Immunology, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences , 320 Yueyang Road, Xuhui District, Shanghai 200031 ,","place":["China"]},{"name":"University of Chinese Academy of Sciences, 1 Yanqihu East Road, Huairou District , Beijing 100039 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