SpatialDE: identification of spatially variable genes

Svensson, Valentine, Teichmann, Sarah A, Stegle, Oliver·2018·Nature Methods
DOI 10.1038/nmeth.4636

Cited by (710)

Items 501–600 of 710

  1. Statistical Methods for Spatially Re-solved Transcriptomic Data Analysis
    琳 王 · 2023 · Bioprocess
  2. A Meta-Review of Spatial Transcriptomics Analysis Software
    Jessica L. Gillespie, Maciej Pietrzak, Min‐Ae Song, Dongjun Chung · 2025 · Cells
  3. Spatial dissimilarity analysis in single-cell transcriptomics
    Quan Shi, Karsten Kristiansen · 2025 · Cell Reports Methods
  4. VISTA uncovers missing gene expression and spatial-induced information for spatial transcriptomic data analysis
    Tianyu Liu, Yingxin Lin, Xiao Luo, Yizhou Sun, Hongyu Zhao · 2026 · Communications Biology
  5. Next generation statistical framework for next generation spatial transcriptomics data
    Fatoumata Mangane, Pierre Bost · 2026 · BMC Methods
  6. Modelling Diffuse Subcellular Protein Structures as Dynamic Social Networks
    Andrew Durden · 2019 · arXiv (Cornell University)
  7. Omics Technologies in Spaceflight: Challenges and Considerations for Applying Single-Cell and Spatially Resolved Gene Expression Technologies to Samples Collected In-Flight
    Eliah G. Overbey, Saswati Das, Henry Cope, Pedro Madrigal, Žaneta Andrusivová, Solène Frapard, Rebecca Klotz, Daniela Bezdan, Ryan T. Scott, Jiwoon Park et al. · 2022 · SSRN Electronic Journal
  8. BayesTME: A unified statistical framework for spatial transcriptomics
    Haoran Zhang, Miranda V. Hunter, Jacqueline Chou, Jeffrey F. Quinn, Mingyuan Zhou, Richard Mark White, Wesley Tansey · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  9. Spatial embryo profiling (STEP) of primate implantation stages
    Sophie Bergmann, Christopher A. Penfold, Erin M. Slatery, Thorsten Boroviak · 2022 · Research Square
  10. Spanve: A Statistical Method for Detecting Downstream-Friendly Spatially Variable Genes in Large-Scale Spatial Transcriptomic Data
    Guoxin Cai, Yichang Chen, Shuqing Chen, Xun Gu, Zhan Mei Zhou · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  11. The Overlooked Role of Specimen Preparation in Bolstering Deep Learning-Enhanced Spatial Transcriptomics Workflows
    Michael Fatemi, Yunrui Lu, Alos Diallo, Gokul Srinivasan, Zarif Azher, Brock C. Christensen, Lucas A. Salas, Gregory J. Tsongalis, Scott M. Palisoul, Laurent Perreard et al. · 2023 · medRxiv
  12. ATAT: Automated Tissue Alignment and Traversal in Spatial Transcriptomics with Self-Supervised Learning
    Steven Song, Emaan Mohsin, Renyu Zhang, Andrey Kuznetsov, Le Shen, Robert L. Grossman, Christopher R. Weber, Aly Azeem Khan · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  13. Detection of spatial chromatin accessibility patterns with inter-cellular correlations
    Xiaoyang Chen, Keyi Li, Xiaoqing Wu, Zhen Li, Qun Jiang, Yanhong Wu, Rui Jiang · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  14. A Universal Framework for Spatial Transcriptomics Data Mining with Interpretable Unsupervised Graph Representation Learning
    Long Liu, Shuyuan Bi, Ning Wang, Minghui Wang · 2024 · SSRN Electronic Journal
  15. Spatial motifs reveal patterns in cellular architecture of complex tissues
    Zainalabedin Samadi, Amjad Askary · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  16. scBSP: A fast and accurate tool for identifying spatially variable genes from spatial transcriptomic data
    Jinpu Li, Yiqing Wang, Mauminah Raina, Chunhui Xu, Li Su, Qi Guo, Qin Ma, Juexin Wang, Dong He Xu · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  17. A DIY guide for image-based spatial transcriptomic: TLS as a case example
    Thomas Defard, Auxence Desrentes, Charles Fouillade, Florian Mueller · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  18. SpaceExpress enables differential spatial transcriptomics with natural coordinate systems
    Yeojin Kim, Abhishek Ojha, Alex W. Schrader, Juyeon Lee, Zijun Wu, Ian M. Traniello, Saumya Jain, Gene E. Robinson, Hee Sun Han, Sihai Dave Zhao et al. · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  19. Guidestar: a spike-in approach to improve RNA detection accuracy in imaging-based spatial transcriptomics
    Jazlynn Xiu Min Tan, Lurong Wang, Wan Yi Seow, Jeeranan Boonruangkan, Mike Huang, Jiamin Toh, Kok Hao Chen, Nigel Chou · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  20. Powerful and accurate case-control analysis of spatial molecular data
    Yakir Reshef, Lakshay Sood, Michelle L. Curtis, Laurie Rumker, Daniel J. Stein, Mukta G. Palshikar, Saba Nayar, Andrew D. Filer, Anna Helena Jonsson, Ilya Korsunsky et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  21. Nearest-neighbor nonnegative spatial factorization to study spatial and temporal transcriptomics
    Priyanka Shrestha, Luis Chumpitaz Diaz, Barbara Elizabeth Engelhardt · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  22. Spatial Metagene Discovery and Associated Molecular Pattern Characterization in Spatial Transcriptomics and Multi-Omics using SEPAR
    Lei Zhang, Ying Zhu, Shuqin Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  23. A Gentle Introduction to Spatial Transcriptomic Analysis with 10X Visium Data
    Jessica L. Gillespie, Juan Xie, Kyeong Joo Jung, Gary Hardiman, Maciej Pietrzak, Dongjun Chung · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  24. A computational framework for mapping isoform landscape and regulatory mechanisms from spatial transcriptomics data
    Jiayu Su, Yiming Qu, Megan D. Schertzer, Haochen Yang, Jiahao Jiang, Tenzin W. Lhakhang, Theodore M. Nelson, Stella Park, Qiliang Lai, Xi Fu et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  25. SimSpace: a comprehensive in-silico spatial omics data simulation and modeling framework
    Tianxiao Zhao, Katherine Zhang, Michelle Hollenberg, Wen Hu Zhou, David Fenyö · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  26. Population-Scale Integration of Spatial Omics Networks for Clinical Prediction and Biological Discovery by SPIN
    Tong Liu, Euiseong Ko, Yiwen Yang, Haowen Wu, Thatchayut Unjitwattana, Suyuan Wang, Jian Kang, Yijun Li, Lana X. Garmire · 2025 · medRxiv
  27. Uncovering directionally and temporally variable genes with STAVAG
    Qunlun Shen, Kuo Gai, Shang Li, Fangkun Yang, Hanbin Cui, Shuqin Zhang, Shihua Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  28. S3R: Modeling spatially varying associations with Spatially Smooth Sparse Regression
    Xinyu Zhou, Pengtao Dang, Xiao Wang, Laura Xianlu Peng, Jen Jen Yeh, Nan Zhang, Brian Neelon, Rosalie C. Sears, Teresa A. Zimmers, Chi Zhang et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  29. Mapping disease critical spatially variable gene programs by integrating spatial transcriptomics with human genetics
    Hanbyul Lee, Haochen Sun, Xuewei Cao, Berke Karaahmet, Zhijian Li, Hans Ulrich-Klein, Mariko F. Taga, Gao T. Wang, Philip L. De Jager, David Alan Bennett et al. · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  30. SpacGPA: annotating spatial transcriptomes through de novo interpretable gene programs
    Yupu Xu, Lirui Chen, Shisong Ma · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  31. Spatial Dependence and Heterogeneity in Molecular Imaging: Moran Quadrant Maps Enable Advanced Spatial-Statistical Analysis
    Léonore E. M. Tideman, Felipe A. Moser, Lukasz G. Migas, Jacquelyn Spathies, Katerina V. Djambazova, Cody R. Marshall, Matthew Schrag, Eric Patrick Skaar, Jeffrey M. Spraggins, Raf Van de Plas · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  32. NicheAgent: LLM-Guided Zero-Shot Niche Identification for Spatial Transcriptomics
    Sajib Acharjee Dip, Liqing Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  33. SparseAEH: Scalable autoregressive expression histology discovery in spatial transcriptomics via sparse Gaussian kernels
    Tianjie Wang, Lingyu Li, Yuanhua Huang · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  34. Unlocking Multi-Sample Differential Expression for Spatial Transcriptomics Data with TESSERA
    Florica Constantine, Zoltan G. Laszik, Sandrine Dudoit, Elizabeth A. Purdom · 2026 · bioRxiv (Cold Spring Harbor Laboratory)
  35. Polar Gini Curve: a Technique to Discover Single-cell Biomarker Using 2D Visual Information
    Thanh Minh Nguyen, Jacob John Jeevan, Nuo Xu, Jake Y. Chen · 2020 · bioRxiv (Cold Spring Harbor Laboratory)
  36. Next Generation Sequencing Methods: Pushing the Boundaries
    Laura A Finnegan, Fiona Crispie, Marcus Joakim Claesson, Paul D. Cotter, John G. Kenny · 2020 · Elsevier eBooks
  37. Model of counsellors leadership and emotional intelligence as predictors of students' social and emotional learning outcomes
    Juliet Yayra Tengey · 2021 · Unisa Institutional Repository (University of South Africa)
  38. Detecting Hot Spots Using GIS Analysis: Case Study of Indonesia's Political Opposition Hashtag
    Bambang Ruswandi, Zulkifli Zulkifli, Raspiani Raspiani, Taufik Edy Sutanto · 2021 · International Conference on Cyber and IT Service Management (CITSM)
  39. SPRI: Spatial Pattern Recognition using Information based method for spatial gene expression data
    Jinxian Hu, Zhi-Rui Hu, Ye Yuan, Hong‐Bin Shen · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  40. SPIRAL: Significant Process InfeRence ALgorithm for single cell RNA-sequencing and spatial transcriptomics
    Hadas Biran, Tamar Hashimshony, Yael Mandel‐Gutfreund, Zohar Yakhini B · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  41. Identification of spatially variable genes with graph cuts
    Ke Zhang, Wanwan Feng, Peng Wang · 2022 · Research Square
  42. Identifying Genes with Location Dependent Noise Variance in Spatial Transcriptomics Data
    Mohammed Abid Abrar, Mohammad Kaykobad, Mohammad Saifur Rahman, Md. Abul Hassan Samee · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  43. Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study
    Michael Fatemi, Eric Feng, Cyril Sharma, Zarif Azher, Tarushii Goel, Ojas A. Ramwala, Scott M. Palisoul, Rachael E. Barney, Laurent Perreard, Fred Kolling et al. · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  44. Cell composition inference and identification of layer-specific transcriptional profiles with POLARIS
    Jiawen Carmen Chen, Tianyou Luo, Min-Zhi Jiang, Jiandong Liu, Gaorav P. Gupta, Yun Li · 2022 · bioRxiv (Cold Spring Harbor Laboratory)
  45. Unraveling Spatial Gene Associations with SEAGAL: a Python Package for Spatial Transcriptomics Data Analysis and Visualization
    Linhua Wang, Chaozhong Liu, Zhandong Liu · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  46. Spatial transcriptomics dimensionality reduction using wavelet bases
    Zhuoyan Xu, Kris Sankaran · 2022 · F1000Research
  47. Finding spatially variable ligand-receptor interactions from spatial transcriptomes
    Shiying Li, Ruohan Wang, Sitong LIU, Shuai Cheng Li · 2023 · Research Square
  48. InGene: Finding influential genes from embeddings of nonlinear dimension reduction techniques
    Chitrita Goswami, N Bhattacharya, Debarka Sengupta · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  49. Identification of treatment-responsive genes in spatial transcriptomics data by leveraging injection site information
    Felicita Pia Masone, Francesco Napolitano · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  50. Finding spatially variable ligand-receptor interactions from spatial transcriptomes
    Shiying Li, Ruohan Wang, Sitong LIU, Shuai Cheng Li · 2023 · Research Square
  51. Exploring the Mosaic-like Tissue Architecture of Kidney Diseases Using Relation Equivariant Graph Neural Networks on Spatially Resolved Transcriptomics
    Mauminah Raina, Hao Cheng, Hari Naga Sai Kiran Suryadevara, Treyden Stransfield, Dong He Xu, Qin Ma, Michael T. Eadon, Juexin Wang · 2023 · bioRxiv (Cold Spring Harbor Laboratory)
  52. Additional file 17 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Yang Xu, Rachel Patton McCord · 2021 · Figshare
  53. Additional file 4 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou · 2022 · Figshare
  54. Additional file 6 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ma, Ying, Xiang Qin Zhou · 2022 · Figshare
  55. Additional file 1 of Feature selection revisited in the single-cell era
    Pengyi Yang, Hao Huang, Liu, Chunlei · 2021 · Figshare
  56. Additional file 16 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Yang Xu, Rachel Patton McCord · 2021 · Figshare
  57. Additional file 1 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ma, Ying, Xiang Qin Zhou · 2022 · Figshare
  58. Additional file 5 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou · 2022 · Figshare
  59. Additional file 2 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou · 2022 · Figshare
  60. Additional file 3 of Modeling zero inflation is not necessary for spatial transcriptomics
    Peiyao Zhao, Jiaqiang Zhu, Ying Ma, Xiang Zhou · 2022 · Figshare
  61. Analysis of the influence of microgravity and space radiation on astronauts’ gene expression: An approach using quantum simulations and fuzzy logic
    Miguel Angel Vargas Cruz · 2024 · Precision Nanomedicine
  62. Lessons from spatial transcriptomics and computational geography in mapping the transcriptome
    Alexis Comber, Eleftherios Zormpas, Rachel A. Queen, Simon Cockell · 2024 · AGILE GIScience Series
  63. Inferring metabolite states from spatial transcriptomes using multiple graph neural network
    Jiaxu Luo, Daosheng Ai, Wenzhi Sun · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  64. A zero-inflated hierarchical generalized transformation model to address non-normality in spatially-informed cell-type deconvolution
    Hunter J. Melton, Jonathan R. Bradley, Chong Wu · 2026 · Biometrics
  65. Identifying Differential Spatial Expression Patterns across Different Slices, Conditions and Developmental Stages with Interpretable Deep Learning
    Yan Cui, Zhiyuan Yuan · 2024 · bioRxiv (Cold Spring Harbor Laboratory)
  66. Cell-specific priors rescue differential gene expression in spatial spot-based technologies
    Ornit Nahman, Timothy J Few-Cooper, Shai S. Shen-Orr · 2024 · Briefings in Bioinformatics
  67. Evaluation of Spatially Variable Genes as Biomarkers in Tumor Initiation and Progression
    Aylin Seher Uzunoğlu, Merve Saide Uzunoğlu, Sümeyya Çapuk, Sevgi Kalkanlı Taş · 2024 · Advances in medical diagnosis, treatment, and care (AMDTC) book series
  68. MuST: Maximizing the Latent Capacity of Spatial Transcriptomics Data with Multi-modality Structure Transformation
    Zelin Zang, Liangyu Li, Yongjie Xu, Jiahao Li, Chenrui Duan, Yi Sun, Zhen Lei, Stan Ziqing Li · 2024 · IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
  69. SpaFun: discovering domain-specific spatial expression patterns and new disease-relevant genes using functional principal component analysis
    Xi Jiang, Yanghong Guo, Lei Guo, Lin Zhong, Jiayi Wang, Guanghua Xiao, Qiwei Li, Lin Xu · 2026 · Briefings in Bioinformatics
  70. Mapping shared and unique features in spatial transcriptomics through multivariate curve resolution
    Albert Menéndez-Pedriza, Mercedes Blázquez, Laia Navarro‐Martín, Joaquim Jaumot · 2025 · Microchemical Journal
  71. From Data-Driven to Expert-Guided: Combining Unsupervised and Semi-supervised Clustering in Spatial Transcriptomics
    Andrea Sottosanti, Sara A. Castiglioni, Davide Risso · 2025 · Springer eBooks
  72. Precise Characterization of Cellular States and Spatial Variable Patterns within Spatial Transcriptomics
    Guangchuang Yu, Shuangbin Xu, Qianwen Wang, Junrui Li, Jia Li, Rui Wang, Liangsheng Zhang, Wenqin Xie, Shaodi Wen, Ming Li et al. · 2025 · Research Square
  73. Single Cell and Spatial Omics and Applications in Toxicology
    David A. Gallegos, Dakota R. Robarts, David S. Umbaugh · 2025 · Elsevier eBooks
  74. CSFeatures improves the identification of cell-type-specific differential features in single-cell and spatial omics data
    Rufeng Li, Yongkang Li, Heyang Hua, Zhen Li, Hongyu Su, Yu Zhang, Yufei Yao, Yidong Wang, Shengquan Chen, Yungang Xu · 2026 · Journal of Advanced Research
  75. Spatial Transcriptomics Domain Identification Algorithm Based on Multi-scale Contrastive Learning
    Keyang Xiao, Jing Wang, Delei Ke, Chun-Hou Zheng · 2025 · Lecture notes in computer science
  76. Semantic consistency-guided patch-wise relation graph reasoning scheme for lung cancer organoid segmentation in brightfield microscopy
    Tianxu Lv, Jiansong Fan, Zexin Chen, Yuan Liu, Jianming Ni, Wei Chu, Xiang Pan · 2025 · Computer Methods and Programs in Biomedicine
  77. spOT-NMF: Optimal Transport-Based Matrix Factorization for Accurate Deconvolution of Spatial Transcriptomics
    Aly O. Abdelkareem, Gurveer S. Gill, Varsha Thoppey Manoharan, Theodore B. Verhey, A. Sorana Morrissy · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  78. Deciphering context-specific gene programs from single-cell and spatial transcriptomics data with DeCEP
    Lin Li, Xianbin Su, Ze‐Guang Han · 2025 · Genome Research
  79. gnSPADE: a reference-free deconvolution method incorporating gene network structures in spatial transcriptomics
    Aoqi Xie, Yuehua Cui · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  80. BISON: bi-clustering of spatial omics data with feature selection
    Bencong Zhu, Alberto Cassese, Marina Vannucci, Michele Guindani, Qiwei Li · 2025 · Bioinformatics
  81. Reference-informed spatial domain detection using weak supervision for spatial transcriptomics
    Xin Ma, Weijia Jin, Qing Lü, Ramon C. Sun, Li Chen · 2026 · Genome Research
  82. DiSTect: a Bayesian model for disease-associated gene discovery and prediction in spatial transcriptomics
    Qicheng Zhao, Anji Deng, Qihuang Zhang · 2025 · Bioinformatics
  83. How to get the most out of your cancer spatial transcriptomics data
    David I. Kaplan, Xiang Yun Guo, Sasuni D Hirimuthugoda, Lachlan Cain, Sirui Weng, David Le, James Comben, Anna Trigos · 2025 · Seminars in Cell and Developmental Biology
  84. Integrating multiomics data for personalized TNBC management
    Unmesh G. Bhamre, Harshali Kothawade, Deepali D. Bhandari, Sunil Vishwanath Amrutkar, Dattatraya Manohar Shinkar · 2025 · Elsevier eBooks
  85. KSRV: a Kernel PCA-Based framework for inferring spatial RNA velocity at single-cell resolution
    He Yan, Jian Wei Jiang, Huahai Qiu, Ya-Zhou Shi, Bengong Zhang · 2025 · Frontiers in Genetics
  86. Can Lightweight LLM Agents Improve Spatial Transcriptomics Annotation?
    Sajib Acharjee Dip, Liqing Zhang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  87. scBrainScope: cross-species multidimensional brain atlas
    Siying Qin, Yuexi Yang, Haoyu Wang, Mengrou Li, Yushan Deng, Yangfeng Chen, Changxiao Li, Lingmin Peng, Linlin Xu, Xiwen Qiu et al. · 2025 · Nucleic Acids Research
  88. Adding highly variable genes to spatially variable genes can improve cell type clustering performance in spatial transcriptomics data
    Yijun Li, Stefan Stanojevic, Bing He, Zheng Jing, Qianhui Huang, Jian Kang, Lana X Garmire · 2025 · Bioinformatics Advances
  89. Benchmarking Cell-Type-Specific Spatially Variable Gene Detection Methods Using a Realistic and Decomposable Simulation Framework
    Weiqi Li, Xinzhou Ge, Yuan Jiang · 2025 · bioRxiv (Cold Spring Harbor Laboratory)
  90. Spatially Regularized Gaussian Mixtures for Clustering Spatial Transcriptomic Data
    Andrea Sottosanti, Davide Risso, Francesco Denti · 2025 · Journal of Classification
  91. geneSCOPE: gene spatial co-occurrence of pairwise expression
    Shicheng Zhang, Koichi Saeki, Hiroshi Haeno · 2026 · Briefings in Bioinformatics
  92. Variational sparse Gaussian-process method for detecting spatially variable genes and cellular interactions in spatial transcriptomics
    Zhicong Wang, Jing Li, Liqing Xie, Yongtian Wang, Tao Wang, Jing Chen, Xuequn Shang, Xingyi Li, Zhaowen Liu, Jialu Hu · 2026 · Briefings in Bioinformatics
  93. Additional file 6 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Xu, Yang, Rachel Patton McCord · 2021 · Figshare
  94. Additional file 11 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Xu, Yang, Rachel Patton McCord · 2021 · Figshare
  95. Additional file 2 of Feature selection revisited in the single-cell era
    Pengyi Yang, Huang, Hao, Liu, Chunlei · 2021 · Figshare
  96. Additional file 1 of SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies
    Zhu, Jiaqiang, Sun, Shiquan, Zhou, Xiang · 2021 · Figshare
  97. Additional file 5 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Xu, Yang, Rachel Patton McCord · 2021 · Figshare
  98. Additional file 10 of CoSTA: unsupervised convolutional neural network learning for spatial transcriptomics analysis
    Xu, Yang, Rachel Patton McCord · 2021 · Figshare
  99. Additional file 2 of SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics
    Zhu, Jiaqiang, Lulu Shang, Zhou, Xiang · 2024 · Figshare
  100. Additional file 3 of SRT-Server: powering the analysis of spatial transcriptomic data
    Yang, Sheng, Zhou, Xiang · 2024 · Figshare