Cell segmentation-free inference of cell types from in situ transcriptomics data
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Roland Eils | Jeongbin Park | Wonyl Choi | Sebastian Tiesmeyer | Brian R. Long | Lars E. Borm | Emma Garren | Thuc Nghi Nguyen | Simone Codeluppi | Matthias Schlesner | Bosiljka Tasic | Naveed Ishaque | R. Eils | T. Nguyen | Bosiljka Tasic | E. Garren | M. Schlesner | S. Codeluppi | Jeongbin Park | Naveed Ishaque | Sebastian Tiesmeyer | Wonyl Choi
[1] Fabian J Theis,et al. Diffusion pseudotime robustly reconstructs lineage branching , 2016, Nature Methods.
[2] Long Cai,et al. Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data , 2019, bioRxiv.
[3] Christopher J. Cronin,et al. Dynamics and Spatial Genomics of the Nascent Transcriptome by Intron seqFISH , 2018, Cell.
[4] R. Satija,et al. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression , 2019, Genome Biology.
[5] Nimrod D. Rubinstein,et al. Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region , 2018, Science.
[6] Lars E. Borm,et al. Molecular Architecture of the Mouse Nervous System , 2018, Cell.
[7] Jens Hjerling-Leffler,et al. Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system , 2016, Science.
[8] Chenglong Xia,et al. Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression , 2019, Proceedings of the National Academy of Sciences.
[9] Takeshi Sakurai,et al. Identification of a population of sleep-active cerebral cortex neurons , 2008, Proceedings of the National Academy of Sciences.
[10] E. Parzen. On Estimation of a Probability Density Function and Mode , 1962 .
[11] Michael L. Waskom,et al. mwaskom/seaborn: v0.9.0 (July 2018) , 2018 .
[12] William Schroeder,et al. The Visualization Toolkit: An Object-Oriented Approach to 3-D Graphics , 1997 .
[13] F. Fujiyama,et al. Demonstration of long‐range GABAergic connections distributed throughout the mouse neocortex , 2005, The European journal of neuroscience.
[14] Hugues Hoppe,et al. New quadric metric for simplifying meshes with appearance attributes , 1999, Proceedings Visualization '99 (Cat. No.99CB37067).
[15] Allan R. Jones,et al. Conserved cell types with divergent features in human versus mouse cortex , 2019, Nature.
[16] Patrik L. Ståhl,et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics , 2016, Science.
[17] S. Teichmann,et al. Exponential scaling of single-cell RNA-seq in the past decade , 2017, Nature Protocols.
[18] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[19] Carolyn R. Bertozzi,et al. Mammalian Y RNAs are modified at discrete guanosine residues with N-glycans , 2019, bioRxiv.
[20] Fusheng Wang,et al. Automated cell segmentation with 3D fluorescence microscopy images , 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).
[21] B. S. Manjunath,et al. Accurate 3D Cell Segmentation Using Deep Features and CRF Refinement , 2019, 2019 IEEE International Conference on Image Processing (ICIP).
[22] Erlend Hodneland,et al. CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation , 2013, Source Code for Biology and Medicine.
[23] Aric Hagberg,et al. Exploring Network Structure, Dynamics, and Function using NetworkX , 2008 .
[24] Evan Z. Macosko,et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution , 2019, Science.
[25] Michael M. Kazhdan,et al. Screened poisson surface reconstruction , 2013, TOGS.
[26] Hannah A. Pliner,et al. Reversed graph embedding resolves complex single-cell trajectories , 2017, Nature Methods.
[27] Guo-Cheng Yuan,et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+ , 2019, Nature.
[28] S. Teichmann,et al. SpatialDE: identification of spatially variable genes , 2018, Nature Methods.
[29] Erik Sundström,et al. RNA velocity of single cells , 2018, Nature.
[30] S. Fortunato,et al. Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.
[31] Richard Bonneau,et al. High-density spatial transcriptomics arrays for in situ tissue profiling , 2019, bioRxiv.
[32] Michael M. Kazhdan,et al. Poisson surface reconstruction , 2006, SGP '06.
[33] Filippo Molinari,et al. Automated Segmentation of Fluorescence Microscopy Images for 3D Cell Detection in human-derived Cardiospheres , 2019, Scientific Reports.
[34] Jisha John,et al. A review on cell detection and segmentation in microscopic images , 2017, 2017 International Conference on Circuit ,Power and Computing Technologies (ICCPCT).
[35] Sebastian J. Streichan,et al. Identification of a neural crest stem cell niche by Spatial Genomic Analysis , 2017, Nature Communications.
[36] 冨岡 良平. Demonstration of long-range GABAergic connections distributed throughout the mouse neocortex , 2005 .
[37] I. Amit,et al. Single-cell spatial reconstruction reveals global division of labor in the mammalian liver , 2016, Nature.
[38] Allan R. Jones,et al. Shared and distinct transcriptomic cell types across neocortical areas , 2018, Nature.
[39] Kan Liu,et al. Giotto, a toolbox for integrative analysis and visualization of spatial expression data , 2020 .
[40] Aaron Watters,et al. Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis , 2018, Science.
[41] S. Linnarsson,et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq , 2015, Science.
[42] Carolina Wählby,et al. In situ sequencing for RNA analysis in preserved tissue and cells , 2013, Nature Methods.
[43] Michael Garland,et al. Surface simplification using quadric error metrics , 1997, SIGGRAPH.
[44] William E. Allen,et al. Three-dimensional intact-tissue sequencing of single-cell transcriptional states , 2018, Science.
[45] Paul Hoffman,et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.
[46] Lucas Pelkmans,et al. Image-based transcriptomics in thousands of single human cells at single-molecule resolution , 2013, Nature Methods.
[47] Fabian J Theis,et al. The Human Cell Atlas , 2017, bioRxiv.
[48] Fabian J Theis,et al. Current best practices in single‐cell RNA‐seq analysis: a tutorial , 2019, Molecular systems biology.
[49] Joakim Lundeberg,et al. Multidimensional transcriptomics provides detailed information about immune cell distribution and identity in HER2+ breast tumors , 2018, bioRxiv.
[50] Eric S. Lander,et al. Compressed sensing for imaging transcriptomics , 2019, bioRxiv.
[51] Kun Zhang,et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues , 2015, Nature Protocols.
[52] Richard A. Davis,et al. Remarks on Some Nonparametric Estimates of a Density Function , 2011 .
[53] Catherine E. Braine,et al. Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis , 2018, Science.
[54] Timur Zhiyentayev,et al. Single-cell in situ RNA profiling by sequential hybridization , 2014, Nature Methods.
[55] L. Cai,et al. In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus , 2016, Neuron.
[56] Cole Trapnell,et al. The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells , 2014, Nature Biotechnology.
[57] X. Zhuang,et al. Spatially resolved, highly multiplexed RNA profiling in single cells , 2015, Science.
[58] Richard Bonneau,et al. High-definition spatial transcriptomics for in situ tissue profiling , 2019, Nature Methods.
[59] Jeffrey M. Perkel,et al. Starfish enterprise: finding RNA patterns in single cells , 2019, Nature.
[60] Fabian J. Theis,et al. destiny: diffusion maps for large-scale single-cell data in R , 2015, Bioinform..
[61] Paolo Cignoni,et al. MeshLab: an Open-Source Mesh Processing Tool , 2008, Eurographics Italian Chapter Conference.
[62] Staci A. Sorensen,et al. Adult Mouse Cortical Cell Taxonomy Revealed by Single Cell Transcriptomics , 2016 .
[63] Lars E. Borm,et al. Spatial organization of the somatosensory cortex revealed by osmFISH , 2018, Nature Methods.