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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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Method: spRefine denoises and imputes spatial transcriptomics with a reference-free framework powered by genomic language model
- Tianyu Liu,
- Tinglin Huang,
- Wengong Jin,
- Tinyi Chu,
- Rex Ying,
- and Hongyu Zhao
Genome Res. February 3, 2026 gr.281001.125; Published in Advance February 3, 2026, doi:10.1101/gr.281001.125
...spRefine denoises and imputes spatial1 transcriptomics with a reference-free framework2 powered by genomic language model3 Tianyu Liu1,2, Tinglin Huang3, Wengong Jin4,5, Tinyi Chu2, Rex4 Ying3, Hongyu Zhao1,2*5 1Interdepartmental Program in Computational Biology &6 Bioinformatics, Yale 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
...of spatial transcriptomics data, each tissue section is decomposed into a collection of discrete locations, referred to as “spots,” at different cellular resolutions depending on the sequencing technology. For scRNA-seq data, each individual cell serves as the fundamental unit of analysis. To unify...
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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: 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
...@shu.edu.cnAbstractThe spatial heterogeneity of gene expression has driven the development of diverse spatial transcriptomics technologies. Here, we present photocleavage and ligation sequencing (PCL-seq), a spatial indexing method utilizing a light-controlled DNA labeling strategy applied to tissue sections. PCL-seq employs...
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Method: QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data
- Xiaoyu Song,
- Yuqing Shang,
- Michelle E. Ehrlich,
- Panos Roussos,
- Guo-Cheng Yuan,
- and Pei Wang
Genome Res. August 2025 35: 1821-1831; Published in Advance June 23, 2025, doi:10.1101/gr.279859.124
...QuadST identifies cell–cell interaction–changed genes in spatially resolved transcriptomics data Xiaoyu Song1, Yuqing Shang1, Michelle E. Ehrlich2, Panos Roussos3,4, Guo-Cheng Yuan5 and Pei Wang6 1Centre for Quantitative Medicine, Duke-NUS Medical School, Singapore 169857; 2Departments of Neurology...
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Research: Developmental transcriptomics in Pristionchus reveals the environmental responsiveness of a plasticity gene-regulatory network
- Shelley Reich,
- Tobias Loschko,
- Julie Jung,
- Samantha Nestel,
- Ralf J. Sommer,
- and Michael S. Werner
Genome Res. July 2025 35: 1560-1573; Published in Advance June 9, 2025, doi:10.1101/gr.279783.124
...yield fewer changes in gene expression than between-environment comparisons. However, we found that mutating or overexpressing individual mouth-form genes still generated substantial transcriptomic differences across development, especially at 60 and 72 h time points (Supplemental Fig. S10A). Notably...
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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: 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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