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In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 33…

Quantitative Methods · Quantitative Biology 2024-10-04 Guanao Yan , Shuo Harper Hua , Jingyi Jessica Li

Spatial variable genes (SVGs) reveal critical information about tissue architecture, cellular interactions, and disease microenvironments. As spatial transcriptomics (ST) technologies proliferate, accurately identifying SVGs across diverse…

Applications · Statistics 2025-10-21 Jiawen Chen , Jinwei Zhang , Dongshen Peng , Yutong Song , Aitong Ruan , Yun Li , Didong Li

The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new…

Quantitative Methods · Quantitative Biology 2021-08-04 Natalie Charitakis , Mirana Ramialison , Hieu T. Nim

Spatial transcriptomics has revolutionized tissue analysis by simultaneously mapping gene expression, spatial topography, and histological context across consecutive tissue sections, enabling systematic investigation of spatial…

Applications · Statistics 2025-10-24 Meng Zhou , Shuangge Ma , Mengyun Wu

A recent technology breakthrough in spatial molecular profiling has enabled the comprehensive molecular characterizations of single cells while preserving spatial information. It provides new opportunities to delineate how cells from…

Applications · Statistics 2021-10-07 Xi Jiang , Qiwei Li , Guanghua Xiao

Recent advancements in spatial transcriptomics technologies allow researchers to simultaneously measure RNA expression levels for hundreds to thousands of genes while preserving spatial information within tissues, providing critical…

Methodology · Statistics 2025-07-31 Catherine Higgins , Jingyi Jessica Li , Michelle Carey

Spatial transcriptomics (ST) technologies enable transcriptome-wide gene expression profiling while preserving spatial resolution, offering unprecedented opportunities to uncover complex spatial structures. Due to the ultra-high…

Applications · Statistics 2026-03-11 Changhu Wang , Qiyun Huang , Zihao Chen , Jin Liu , Ruibin Xi

Human and animal tissues consist of heterogeneous cell types that organize and interact in highly structured manners. Bulk and single-cell sequencing technologies remove cells from their original microenvironments, resulting in a loss of…

Quantitative Methods · Quantitative Biology 2022-02-08 Boxiang Liu , Yanjun Li , Liang Zhang

Single-cell RNA-sequencing technologies may provide valuable insights to the understanding of the composition of different cell types and their functions within a tissue. Recent technologies such as spatial transcriptomics, enable the…

Applications · Statistics 2023-05-16 Arhit Chakrabarti , Yang Ni , Bani K. Mallick

Identifying genes that display spatial patterns is critical to investigating expression interactions within a spatial context and further dissecting biological understanding of complex mechanistic functionality. Despite the increase in…

Methodology · Statistics 2025-10-06 Mingcong Wu , Yang Li , Shuangge Ma , Mengyun Wu

Spatially resolved transcriptomics (ST) measures gene expression along with the spatial coordinates of the measurements. The analysis of ST data involves significant computation complexity. In this work, we propose gene expression…

Genomics · Quantitative Biology 2022-05-24 Zhuoyan Xu , Kris Sankaran

In order to understand the complexities of cellular biology, researchers are interested in two important metrics: the genetic expression information of cells and their spatial coordinates within a tissue sample. However, state-of-the art…

Machine Learning · Computer Science 2023-11-02 J. Ding , S. N. Zaman , P. Y. Chen , D. Wang

Identifying disease-indicative genes is critical for deciphering disease mechanisms and has attracted significant interest in biomedical research. Spatial transcriptomics offers unprecedented insights for the detection of disease-specific…

Methodology · Statistics 2024-09-05 Qicheng Zhao , Qihuang Zhang

Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling of histopathology, providing valuable insights into…

Computer Vision and Pattern Recognition · Computer Science 2025-06-11 Junzhuo Liu , Markus Eckstein , Zhixiang Wang , Friedrich Feuerhake , Dorit Merhof

Advances in spatial transcriptomics (ST) technologies enable systematic molecular characterization of tumor microenvironment, tumor gradients and gene regulatory networks. Cancer progression is known to vary along pathological gradients,…

Spatial transcriptomics technologies enable the measurement of gene expression with spatial context, providing opportunities to understand how gene regulatory networks vary across tissue regions. However, existing graphical models focus…

Methodology · Statistics 2025-12-15 Trisha Dawn , Yang Ni

Spatial transcriptomics is a modern sequencing technology that allows the measurement of the activity of thousands of genes in a tissue sample and map where the activity is occurring. This technology has enabled the study of the so-called…

Methodology · Statistics 2022-09-15 Andrea Sottosanti , Davide Risso

Spatial transcriptomics (ST) is a novel technique that simultaneously captures pathological images and gene expression profiling with spatial coordinates. Since ST is closely related to pathological features such as disease subtypes, it may…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Kazuya Nishimura , Ryoma Bise , Yasuhiro Kojima

The advent of next-generation sequencing-based spatially resolved transcriptomics (SRT) techniques has reshaped genomic studies by enabling high-throughput gene expression profiling while preserving spatial and morphological context.…

Applications · Statistics 2025-02-20 Bencong Zhu , Alberto Cassese , Marina Vannucci , Michele Guindani , Qiwei Li

Spatially resolved transcriptomics is a fast-developing set of technologies that enables the measurement of localized gene expression across spatial locations in a sample. Detecting spatially varying genes is critical for analyzing such…

Applications · Statistics 2026-04-22 Pritam Dey , Rajarshi Guhaniyogi , Yang Ni , Bani K. Mallick
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