{"title":"sCCIgen:用于细胞-细胞相互作用研究的高保真空间分辨转录组学数据模拟器","authors":"Xiaoyu Song, Joselyn C. Chavez-Fuentes, Weiping Ma, Weijia Fu, Sujung Crystal Shin, Pei Wang, Guo-Cheng Yuan","doi":"10.1186/s13059-025-03762-9","DOIUrl":null,"url":null,"abstract":"Spatially resolved transcriptomics (SRT) facilitates the study of cell–cell interactions within native tissue environments. To support method development and benchmarking, we introduce sCCIgen, a real-data-based simulator that generates high-fidelity synthetic SRT data with known interaction features. sCCIgen preserves transcriptomic and spatial characteristics and provides key interaction features, including cell colocalization, spatial dependence of gene expression, and gene–gene interactions between neighboring cells. It supports input from SRT data, single-cell expression data alone, and unpaired expression and spatial data. sCCIgen is interactive, user-friendly, reproducible, and well-documented for studying cellular interactions and spatial biology.","PeriodicalId":12611,"journal":{"name":"Genome Biology","volume":"27 1","pages":""},"PeriodicalIF":10.1000,"publicationDate":"2025-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell–cell interaction studies\",\"authors\":\"Xiaoyu Song, Joselyn C. Chavez-Fuentes, Weiping Ma, Weijia Fu, Sujung Crystal Shin, Pei Wang, Guo-Cheng Yuan\",\"doi\":\"10.1186/s13059-025-03762-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spatially resolved transcriptomics (SRT) facilitates the study of cell–cell interactions within native tissue environments. To support method development and benchmarking, we introduce sCCIgen, a real-data-based simulator that generates high-fidelity synthetic SRT data with known interaction features. sCCIgen preserves transcriptomic and spatial characteristics and provides key interaction features, including cell colocalization, spatial dependence of gene expression, and gene–gene interactions between neighboring cells. It supports input from SRT data, single-cell expression data alone, and unpaired expression and spatial data. sCCIgen is interactive, user-friendly, reproducible, and well-documented for studying cellular interactions and spatial biology.\",\"PeriodicalId\":12611,\"journal\":{\"name\":\"Genome Biology\",\"volume\":\"27 1\",\"pages\":\"\"},\"PeriodicalIF\":10.1000,\"publicationDate\":\"2025-10-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Genome Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1186/s13059-025-03762-9\",\"RegionNum\":1,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Genome Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1186/s13059-025-03762-9","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
sCCIgen: a high-fidelity spatially resolved transcriptomics data simulator for cell–cell interaction studies
Spatially resolved transcriptomics (SRT) facilitates the study of cell–cell interactions within native tissue environments. To support method development and benchmarking, we introduce sCCIgen, a real-data-based simulator that generates high-fidelity synthetic SRT data with known interaction features. sCCIgen preserves transcriptomic and spatial characteristics and provides key interaction features, including cell colocalization, spatial dependence of gene expression, and gene–gene interactions between neighboring cells. It supports input from SRT data, single-cell expression data alone, and unpaired expression and spatial data. sCCIgen is interactive, user-friendly, reproducible, and well-documented for studying cellular interactions and spatial biology.
Genome BiologyBiochemistry, Genetics and Molecular Biology-Genetics
CiteScore
21.00
自引率
3.30%
发文量
241
审稿时长
2 months
期刊介绍:
Genome Biology stands as a premier platform for exceptional research across all domains of biology and biomedicine, explored through a genomic and post-genomic lens.
With an impressive impact factor of 12.3 (2022),* the journal secures its position as the 3rd-ranked research journal in the Genetics and Heredity category and the 2nd-ranked research journal in the Biotechnology and Applied Microbiology category by Thomson Reuters. Notably, Genome Biology holds the distinction of being the highest-ranked open-access journal in this category.
Our dedicated team of highly trained in-house Editors collaborates closely with our esteemed Editorial Board of international experts, ensuring the journal remains on the forefront of scientific advances and community standards. Regular engagement with researchers at conferences and institute visits underscores our commitment to staying abreast of the latest developments in the field.