{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T13:34:37Z","timestamp":1784036077358,"version":"3.55.0"},"reference-count":64,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,15]],"date-time":"2024-03-15T00:00:00Z","timestamp":1710460800000},"content-version":"vor","delay-in-days":53,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002855","name":"Ministry of Science and Technology of the People\u2019s Republic of China","doi-asserted-by":"publisher","award":["2021ZD0201900"],"award-info":[{"award-number":["2021ZD0201900"]}],"id":[{"id":"10.13039\/501100002855","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12090052"],"award-info":[{"award-number":["12090052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Foundation of Fujian Province of China","award":["2023\u00a0J05002"],"award-info":[{"award-number":["2023\u00a0J05002"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["20720230017"],"award-info":[{"award-number":["20720230017"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,1,22]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool for investigating cellular heterogeneity through high-throughput analysis of individual cells. Nevertheless, challenges arise from prevalent sequencing dropout events and noise effects, impacting subsequent analyses. Here, we introduce a novel algorithm, Single-cell Gene Importance Ranking (scGIR), which utilizes a single-cell gene correlation network to evaluate gene importance. The algorithm transforms single-cell sequencing data into a robust gene correlation network through statistical independence, with correlation edges weighted by gene expression levels. We then constructed a random walk model on the resulting weighted gene correlation network to rank the importance of genes. Our analysis of gene importance using PageRank algorithm across nine authentic scRNA-seq datasets indicates that scGIR can effectively surmount technical noise, enabling the identification of cell types and inference of developmental trajectories. We demonstrated that the edges of gene correlation, weighted by expression, play a critical role in enhancing the algorithm\u2019s performance. Our findings emphasize that scGIR outperforms in enhancing the clustering of cell subtypes, reverse identifying differentially expressed marker genes, and uncovering genes with potential differential importance. Overall, we proposed a promising method capable of extracting more information from single-cell RNA sequencing datasets, potentially shedding new lights on cellular processes and disease mechanisms.<\/jats:p>","DOI":"10.1093\/bib\/bbae091","type":"journal-article","created":{"date-parts":[[2024,3,15]],"date-time":"2024-03-15T07:03:26Z","timestamp":1710486206000},"source":"Crossref","is-referenced-by-count":10,"title":["scGIR: deciphering cellular heterogeneity via gene ranking in single-cell weighted gene correlation networks"],"prefix":"10.1093","volume":"25","author":[{"given":"Fei","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Physics, Anhui Normal University , Wuhu 241002 , China"},{"name":"Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences , Wenzhou 325001 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huan","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Applied Genomics, Fuzhou University , Fuzhou 350108 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai","family":"Lin","sequence":"additional","affiliation":[{"name":"Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences , Wenzhou 325001 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jun","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Physics, Anhui Normal University , Wuhu 241002 , China"},{"name":"School of Medical Imageology, Wannan Medical College , Wuhu 241002 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Cheng","sequence":"additional","affiliation":[{"name":"Department of Physics , and Fujian Provincial Key Lab for Soft Functional Materials Research, , Xiamen 361005 , China"},{"name":"Xiamen University , and Fujian Provincial Key Lab for Soft Functional Materials Research, , Xiamen 361005 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiqian","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Physics, Anhui Normal University , Wuhu 241002 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Physics , and Fujian Provincial Key Lab for Soft Functional Materials Research, , Xiamen 361005 , China"},{"name":"Xiamen University , and Fujian Provincial Key Lab for Soft Functional Materials Research, , Xiamen 361005 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8712-0544","authenticated-orcid":false,"given":"Jianwei","family":"Shuai","sequence":"additional","affiliation":[{"name":"Wenzhou Institute and Wenzhou Key Laboratory of Biophysics, University of Chinese Academy of Sciences , Wenzhou 325001 , China"},{"name":"Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health) , Wenzhou 325001 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,3,14]]},"reference":[{"key":"2024031506425765500_ref1","doi-asserted-by":"crossref","first-page":"S6","DOI":"10.1038\/nmeth.1557","article-title":"Development and applications of single-cell transcriptome analysis","volume":"8","author":"Tang","year":"2011","journal-title":"Nat Methods"},{"key":"2024031506425765500_ref2","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1038\/nature14966","article-title":"Single-cell messenger RNA sequencing reveals rare intestinal cell types","volume":"525","author":"Grun","year":"2015","journal-title":"Nature"},{"key":"2024031506425765500_ref3","doi-asserted-by":"crossref","first-page":"618","DOI":"10.1038\/nrg3542","article-title":"Single-cell sequencing-based technologies will revolutionize whole-organism 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