17 papers · ranked by Valyu relevance
Cameron G. Williams, Hyun Jae Lee, Takahiro Asatsuma, Roser Vento-Tormo + 1 more
'Roser Vento-Tormo' 'Ashraful Haque'] Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over the past decade, particularly in developmental biology, cancer, immunology, and neuroscience. Most commercially available scRNA-seq protocols require cells to be recovered intact and viable…
Linlin Zhang, Dongsheng Chen, Dongli Song, Xiaoxia Liu + 3 more
'Xun Xu' 'Xiangdong Wang'] The combination of spatial transcriptomics (ST) and single cell RNA sequencing (scRNA-seq) acts as a pivotal component to bridge the pathological phenomes of human tissues with molecular alterations, defining in situ intercellular molecular communications and knowledge on spatiotemporal…
Jun Du, Yu-Chen Yang, Zhi-Jie An, Ming-Hui Zhang + 4 more
'Zou-Fang Huang' 'Ye Yuan' 'Jian Hou'] Spatial transcriptomics technologies developed in recent years can provide various information including tissue heterogeneity, which is fundamental in biological and medical research, and have been making significant breakthroughs. Single-cell RNA sequencing (scRNA-seq) cannot…
Benjamin L. Walker, Zixuan Cang, Honglei Ren, Eric Bourgain-Chang + 1 more
'Qing Nie'] The rapid development of spatial transcriptomics (ST) techniques has allowed the measurement of transcriptional levels across many genes together with the spatial positions of cells. This has led to an explosion of interest in computational methods and techniques for harnessing both spatial and…
Jiaqiang Zhu, Shiquan Sun, Xiang Zhou
Spatial transcriptomic studies are becoming increasingly common and large, posing important statistical and computational challenges for many analytic tasks. Here, we present SPARK-X, a non-parametric method for rapid and effective detection of spatially expressed genes in large spatial transcriptomic studies. SPARK-X…
Zhiwei Fan, Yangyang Luo, Huifen Lu, Tiangang Wang + 4 more
'Weiling Zhao' 'Pora Kim' 'Xiaobo Zhou'] Title: Abstract In recent years, the explosive growth of spatial technologies has enabled the characterization of spatial heterogeneity of tissue architectures. Compared to traditional sequencing, spatial transcriptomics reserves the spatial information of each captured location…
Yang Jin, Yuanli Zuo, Gang Li, Wenrong Liu + 5 more
'Xin Fu' 'Xiaojun Yao' 'Yong Peng'] Malignant tumors have increasing morbidity and high mortality, and their occurrence and development is a complicate process. The development of sequencing technologies enabled us to gain a better understanding of the underlying genetic and molecular mechanisms in tumors. In recent…
Dongshan Ya, Yingmei Zhang, Qi Cui, Yanlin Jiang + 6 more
'Ning Tian' 'Wenjing Xiang' 'Xiaohui Lin' 'Qinghua Li' 'Rujia Liao'] Spatial transcriptome technology acquires gene expression profiles while retaining spatial location information, it displays the gene expression properties of cells in situ. Through the investigation of cell heterogeneity, microenvironment, function…
Helena L. Crowell, Yixing Dong, Ilaria Billato, Peiying Cai + 30 more
Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows…
Teia Noel, Qingbo S. Wang, Anna Greka, Jamie L. Marshall
Spatial transcriptomic technologies capture genome-wide readouts across biological tissue space. Moreover, recent advances in this technology, including Slide-seqV2, have achieved spatial transcriptomic data collection at a near-single cell resolution. To-date, a repertoire of computational tools has been developed to…
Jessica Gillespie, Maciej Pietrzak, Min-Ae Song, Dongjun Chung + 1 more
'Jérôme Eeckhoute'] Spatial transcriptomics combines gene expression data with spatial coordinates to allow for the discovery of detailed RNA localization, study development, investigating the tumor microenvironment, and creating a tissue atlas. A large range of spatial transcriptomics software is available, with…
Shicheng Zhang, Koichi Saeki, Hiroshi Haeno
Spatial transcriptomics captures context-dependent gene expression; however, existing workflows do not consistently account for measurement scale and often rely on a user-defined spatial neighbor graph, making results sensitive to this choice and limiting cross-study comparability. We present geneSCOPE (gene Spatial…
Jiyuan Yang, Nana Wei, Yang Qu, Congcong Hu + 5 more
Spatial transcriptomics (ST) has revolutionized our approaches to understanding cellular heterogeneity, the interplay between gene expression and cellular environment, and the location-specificity of gene expression within complex tissues (, , , ). Unlike traditional single-cell RNA-sequencing (scRNA-seq) technologies…
Matthew N. Bernstein, Zijian Ni, Aman Prasad, Jared Brown + 4 more
'Chitrasen Mohanty' 'Ron Stewart' 'Michael A. Newton' 'Christina Kendziorski'] Title: Summary Recent advances in spatially resolved transcriptomics technologies enable both the measurement of genome-wide gene expression profiles and their mapping to spatial locations within a tissue. A first step in spatial…
Braulio Valdebenito-Maturana, Cristina Guatimosim, Mónica Alejandra Carrasco, Juan Carlos Tapia + 2 more
'Mónica Alejandra Carrasco' 'Juan Carlos Tapia' 'Benoît Chénais' 'Frank M. You'] Spatial transcriptomics (ST) is transforming the way we can study gene expression and its regulation through position-specific resolution within tissues. However, as in bulk RNA-Seq, transposable elements (TEs) are not being studied due to…
Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou
Background Spatial transcriptomics are a set of new technologies that profile gene expression on tissues with spatial localization information. With technological advances, recent spatial transcriptomics data are often in the form of sparse counts with an excessive amount of zero values. Results We perform a…
Theodore Alexandrov, Julio Saez‐Rodriguez, Sinem K Saka
Spatial omics has emerged as a rapidly growing and fruitful field with hundreds of publications presenting novel methods for obtaining spatially resolved information for any omics data type on spatial scales ranging from subcellular to organismal. From a technology development perspective, spatial omics is a highly…