{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T20:33:46Z","timestamp":1772138026528,"version":"3.50.1"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,5,21]],"date-time":"2024-05-21T00:00:00Z","timestamp":1716249600000},"content-version":"vor","delay-in-days":55,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Basic Science Research Program","award":["2021R1C1C1006336"],"award-info":[{"award-number":["2021R1C1C1006336"]}]},{"name":"Bio & Medical Technology Development Program","award":["2021M3A9G8022959"],"award-info":[{"award-number":["2021M3A9G8022959"]}]},{"name":"Ministry of Science"},{"DOI":"10.13039\/100010669","name":"ICT","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001321","name":"National Research Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001321","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Korea Health Technology R&D Project"},{"DOI":"10.13039\/501100003710","name":"Korea Health Industry Development Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003710","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Health & Welfare","award":["HR22C141105"],"award-info":[{"award-number":["HR22C141105"]}]},{"name":"GIST Research Institute"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>The normalization of RNA sequencing data is a primary step for downstream analysis. The most popular method used for the normalization is the trimmed mean of M values (TMM) and DESeq. The TMM tries to trim away extreme log fold changes of the data to normalize the raw read counts based on the remaining non-deferentially expressed genes. However, the major problem with the TMM is that the values of trimming factor M are heuristic. This paper tries to estimate the adaptive value of M in TMM based on Jaeckel\u2019s Estimator, and each sample acts as a reference to find the scale factor of each sample. The presented approach is validated on SEQC, MAQC2, MAQC3, PICKRELL and two simulated datasets with two-group and three-group conditions by varying the percentage of differential expression and the number of replicates. The performance of the present approach is compared with various state-of-the-art methods, and it is better in terms of area under the receiver operating characteristic curve and differential expression.<\/jats:p>","DOI":"10.1093\/bib\/bbae241","type":"journal-article","created":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T08:43:15Z","timestamp":1715244195000},"source":"Crossref","is-referenced-by-count":14,"title":["Normalization of RNA-Seq data using adaptive trimmed mean with multi-reference"],"prefix":"10.1093","volume":"25","author":[{"given":"Vikas","family":"Singh","sequence":"first","affiliation":[{"name":"School of Life Sciences, Gwangju Institute of Science and Technology , 123 Cheomdan-gwagiro, 61005, Gwangju , South Korea"}]},{"given":"Nikhil","family":"Kirtipal","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Gwangju Institute of Science and Technology , 123 Cheomdan-gwagiro, 61005, Gwangju , South Korea"}]},{"given":"Byeongsop","family":"Song","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Gwangju Institute of Science and Technology , 123 Cheomdan-gwagiro, 61005, Gwangju , South Korea"}]},{"given":"Sunjae","family":"Lee","sequence":"additional","affiliation":[{"name":"School of Life Sciences, Gwangju Institute of Science and Technology , 123 Cheomdan-gwagiro, 61005, Gwangju , South Korea"}]}],"member":"286","published-online":{"date-parts":[[2024,5,20]]},"reference":[{"key":"2024052108373359400_ref1","doi-asserted-by":"crossref","DOI":"10.1155\/2015\/621690","article-title":"The impact of normalization methods on RNA-Seq data analysis","volume":"2015","author":"Zyprych-Walczak","year":"2015","journal-title":"Biomed Res Int"},{"key":"2024052108373359400_ref2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-015-0679-0","article-title":"Quantro: a data-driven approach to guide the choice of an appropriate normalization 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