Searching journal content for articles similar to Dries et al. 31 (10): 1706.

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Method: Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method
- Quanyou Cai,
- Lihui Lin,
- Xin Liu,
- and Jiekai Chen
Genome Res. November 2025 35: 2513-2526; Published in Advance October 22, 2025, doi:10.1101/gr.280532.125
.... Corresponding authors: chen_jiekai@gibh.ac.cn, lin_lihui@gibh.ac.cnAbstractIntegration of single-cell and spatial transcriptomes represents a fundamental strategy to enhance spatial data quality. However, existing methods for mapping single-cell data to spatial coordinates struggle with large-scale data sets...
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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
..., Pittsburgh, Pennsylvania 15213, USA Corresponding authors: jianma@cs.cmu.edu, skrieger@andrew.cmu.eduAbstractSpatial transcriptomics (ST) has transformed our understanding of tissue architecture and cellular interactions, but integrating ST data across platforms remains challenging due to differences in gene...
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Research: Transcriptomic landscape of transposable elements reveals LTR7-PLAAT4 as a potential oncogene and therapeutic target in pancreatic adenocarcinoma
- Meilong Shi,
- Chuanqi Teng,
- Shan Zhang,
- Xiaobo He,
- Lingyun Xu,
- Fengxian Han,
- Rongqi Wen,
- Ganjun Yu,
- Jingwen Liu,
- Yang Feng,
- Yanfeng Wu,
- Yan Ren,
- Gang Jin,
- and Jing Li
Genome Res. February 2026 36: 275-290; Published in Advance January 8, 2026, doi:10.1101/gr.280528.125
...), and more recently, (spatial) single-cell sequencing approaches (Moncada et al. 2020; Ma and Zhou 2022). Recent advances in organoid models represent a transformative development in cancer research. Organoids, cultured in vitro, retain self-renewal and self-organizing capabilities that mimic the structure...
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Method: Spatial domain detection using contrastive self-supervised learning for spatial multi-omics technologies
- Jianing Yao,
- Jinglun Yu,
- Brian Caffo,
- Stephanie C. Page,
- Keri Martinowich,
- and Stephanie C. Hicks
Genome Res. July 2025 35: 1621-1632; Published in Advance May 20, 2025, doi:10.1101/gr.279380.124
...in Healthcare, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: shicks19@jhu.eduAbstractRecent advances in spatially resolved single-omic and multi-omics technologies have led to the emergence of computational tools to detect and predict spatial domains. Additionally, histological...
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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: 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: Efficient integration of spatial omics data for joint domain detection, matching, and alignment with stMSA
- Han Shu,
- Jing Chen,
- Chang Xu,
- Jialu Hu,
- Yongtian Wang,
- Jiajie Peng,
- Qinghua Jiang,
- Xuequn Shang,
- and Tao Wang
Genome Res. October 2025 35: 2285-2299; Published in Advance August 14, 2025, doi:10.1101/gr.280584.125
..., providing detailed views of the transcriptome in spatial perspective (Asp et al. 2020). Recently, cellular indexing of transcriptomes and epitopes by sequencing (spatial CITE-seq) (Liu et al. 2023) has emerged as a significant advancement in SOs. This technique integrates RNA sequencing with the measurement...
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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
....Thus, PCL-seq represents not only a significant advancement in spatial transcriptomics but also an adaptable foundation for future developments in multiomics technologies. Its combination of cost-effectiveness, reproducibility, and flexibility positions it as an essential tool for advancing our...
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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: 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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