Searching journal content for articles similar to van Beijnum et al. 33 (8): 1424.

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Method: Unified integration of spatial transcriptomics across platforms with LLOKI
- Ellie Haber,
- Ajinkya Deshpande,
- Jian Ma,
- and Spencer Krieger
Genome Res. December 2025 35: 2722-2733; Published in Advance November 13, 2025, doi:10.1101/gr.280803.125
...GENE (CZI Cell Science Program et al. 2025), and the Human Cell Atlas (Regev et al. 2017). Similarly, integrating spatial transcriptomics (ST) data sets, which contain both spatial coordinates and gene expression, enables comparative analysis across samples, technologies, and conditions, revealing cellular...
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Method: Deciphering context-specific gene programs from single-cell and spatial transcriptomics data with DeCEP
- Lin Li,
- Xianbin Su,
- and Ze-Guang Han
Genome Res. October 2025 35: 2300-2315; Published in Advance August 21, 2025, doi:10.1101/gr.279689.124
.... Recent advancements in single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) technologies have empowered the comprehensive characterization of gene programs at both single-cell and spatial resolutions. Here, we present DeCEP, a computational framework designed to characterize context...
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Method: STCC enhances spatial domain detection through consensus clustering of spatial transcriptomics data
- Congcong Hu,
- Nana Wei,
- Jiyuan Yang,
- Hua-Jun Wu,
- and Xiaoqi Zheng
Genome Res. June 2025 35: 1415-1428; Published in Advance May 12, 2025, doi:10.1101/gr.280031.124
..., Peking University, Beijing 100191, China; 5Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China Corresponding authors: hjwu@pku.edu.cn, xqzheng@shsmu.edu.cnAbstractThe rapid advance of spatially resolved transcriptomics...
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Method: High-resolution spatial transcriptomics in fixed tissue using a cost-effective PCL-seq workflow
- Xue Dong,
- Mengzhu Hu,
- Xiaonan Cui,
- Wenjian Zhou,
- Jingtao Cai,
- Guangyao Mao,
- and Weiyang Shi
Genome Res. September 2025 35: 2052-2063; Published in Advance August 5, 2025, doi:10.1101/gr.279906.124
..., particularly ROI-based methods, has emerged as a powerful approach to overcome these challenges. By focusing on specific anatomical regions or cell types within a spatial context, ROI-based transcriptomic analysis enables precise profiling of gene expression, revealing molecular differences that remain obscure...
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Research: Single-cell spatial transcriptomics reveals a dystrophic trajectory following a developmental bifurcation of myoblast cell fates in facioscapulohumeral muscular dystrophy
- Lujia Chen,
- Xiangduo Kong,
- Kevin G. Johnston,
- Ali Mortazavi,
- Todd C. Holmes,
- Zhiqun Tan,
- Kyoko Yokomori,
- and Xiangmin Xu
Genome Res. May 2024 34: 665-679; Published in Advance May 22, 2024, doi:10.1101/gr.278717.123
...percentage of cells, requiring single-cell analysis. However, single-cell/nucleus RNA-seq cannot fully capture the transcriptome of multinucleated large myotubes. To circumvent these issues, we use multiplexed error-robust fluorescent in situ hybridization (MERFISH) spatial transcriptomics that allows...
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Method: Kernel-bounded clustering for spatial transcriptomics enables scalable discovery of complex spatial domains
- Hang Zhang,
- Yi Zhang,
- Kai Ming Ting,
- Jie Zhang,
- and Qiuran Zhao
Genome Res. February 2025 35: 355-367; Published in Advance February 5, 2025, doi:10.1101/gr.278983.124
...to this work. Corresponding authors: tingkm@nju.edu.cn, zhangj_ai@nju.edu.cnAbstractSpatial transcriptomics are a collection of technologies that have enabled characterization of gene expression profiles and spatial information in tissue samples. Existing methods for clustering spatial transcriptomics data...
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Method: Dissecting multilayer cell–cell communications with signaling feedback loops from spatial transcriptomics data
- Lulu Yan,
- Jinyu Cheng,
- Qing Nie,
- and Xiaoqiang Sun
Genome Res. June 2025 35: 1400-1414; Published in Advance April 22, 2025, doi:10.1101/gr.279857.124
...Dissecting multilayer cell–cell communications with signaling feedback loops from spatial transcriptomics data Lulu Yan1,4, Jinyu Cheng2,4, Qing Nie3 and Xiaoqiang Sun1 1School of Mathematics, Sun Yat-sen University, Guangzhou 510275, China; 2Zhongshan School of Medicine, Sun Yat-sen University...
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Method: Joint imputation and deconvolution of gene expression across spatial transcriptomics platforms
- Hongyu Zheng,
- Hirak Sarkar,
- and Benjamin J. Raphael
Genome Res. December 2025 35: 2734-2743; Published in Advance November 17, 2025, doi:10.1101/gr.280555.125
.... Order determined by a coin flip. Corresponding author: braphael@princeton.eduAbstractSpatially resolved transcriptomics (SRT) technologies measure gene expression across thousands of spatial locations within a tissue slice. Multiple SRT technologies are currently available and others are in active...
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Method: Label-free selection of marker genes in single-cell and spatial transcriptomics with geneCover
- An Wang,
- Stephanie Hicks,
- Donald Geman,
- and Laurent Younes
Genome Res. December 2025 35: 2744-2755; Published in Advance November 12, 2025, doi:10.1101/gr.280539.125
.... We evaluate the performance of geneCover across various scRNA-seq and spatial transcriptomics data sets, comparing it to other label-free algorithms to highlight its utility and potential in diverse biological contexts.The identification of marker genes plays a critical role in advancing our...
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Method: Harnessing agent-based frameworks in CellAgentChat to unravel cell–cell interactions from single-cell and spatial transcriptomics
- Vishvak Raghavan,
- Yumin Zheng,
- Yue Li,
- and Jun Ding
Genome Res. July 2025 35: 1646-1663; Published in Advance May 2, 2025, doi:10.1101/gr.279771.124
...over short time frames. Our evaluation of CellAgentChat, using several publicly available scRNA-seq and spatial transcriptomics data sets, reveal superior CCI inference compared to other benchmarked methods. Together, we introduce a new framework based on ABMs for future advancements in the study...
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