{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T11:49:36Z","timestamp":1782301776810,"version":"3.54.5"},"reference-count":7,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T00:00:00Z","timestamp":1759968000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000057","name":"National Institute of General Medical Sciences","doi-asserted-by":"crossref","award":["R35GM140888"],"award-info":[{"award-number":["R35GM140888"]}],"id":[{"id":"10.13039\/100000057","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational Biology"],"published-print":{"date-parts":[[2026,1,1]]},"abstract":"<jats:p>\n                    Metacell partitioning is a common preprocessing step in single-cell data analysis, used to reduce sparsity by aggregating similar cells. However, existing metacell partitioning algorithms may inadvertently group heterogeneous cells, potentially biasing downstream analyses. The resulting metacell partitions can vary substantially with different hyperparameter settings, leaving users uncertain about which result to trust. The\n                    <jats:monospace>mcRigor<\/jats:monospace>\n                    R package offers a statistical method for evaluating and optimizing metacell partitioning in single-cell data analysis. This article provides instructions for installing and using\n                    <jats:monospace>mcRigor<\/jats:monospace>\n                    to support more rigorous and interpretable metacell-based workflows.\n                  <\/jats:p>","DOI":"10.1177\/15578666251383561","type":"journal-article","created":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T15:16:24Z","timestamp":1760022984000},"page":"43-47","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["<tt>mcRigor<\/tt>\n                    : A Statistical Software Package for Evaluating and Optimizing Metacell Partitioning in Single-Cell Data Analysis"],"prefix":"10.1177","volume":"33","author":[{"given":"Pan","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Statistics and Data Science, University of California, Los Angeles, California, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9288-5648","authenticated-orcid":false,"given":"Jingyi Jessica","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Statistics and Data Science, University of California, Los Angeles, California, USA."}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,10,9]]},"reference":[{"key":"e_1_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-019-1812-2"},{"key":"e_1_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-022-02667-1"},{"key":"e_1_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-022-04861-1"},{"key":"e_1_3_3_5_1","doi-asserted-by":"publisher","DOI":"10.1038\/s44320-024-00045-6"},{"key":"e_1_3_3_6_1","article-title":"mcRigor: A statistical method to enhance the rigor of metacell partitioning in single-cell data analysis","author":"Liu P","year":"2025","unstructured":"Liu P, , Li JJ. mcRigor: A statistical method to enhance the rigor of metacell partitioning in single-cell data analysis. Nat Comms, 2025;16:8602.","journal-title":"Nat Comms"},{"key":"e_1_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-90252-9_44"},{"key":"e_1_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41587-023-01716-9"}],"container-title":["Journal of Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/15578666251383561","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/15578666251383561","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/15578666251383561","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T11:16:33Z","timestamp":1782299793000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/15578666251383561"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,9]]},"references-count":7,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1,1]]}},"alternative-id":["10.1177\/15578666251383561"],"URL":"https:\/\/doi.org\/10.1177\/15578666251383561","relation":{},"ISSN":["1066-5277","1557-8666"],"issn-type":[{"value":"1066-5277","type":"print"},{"value":"1557-8666","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,9]]}}}