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Splotch: Robust estimation of aligned spatial temporal gene expression data

Tarmo Äijö, Silas Maniatis, Sanja Vickovic, Kristy Kang, Miguel Cuevas, Catherine Braine, Hemali Phatnani, Joakim Lundeberg, View ORCID ProfileRichard Bonneau
doi: https://doi.org/10.1101/757096
Tarmo Äijö
1Center for Computational Biology, Flatiron Institute, New York, NY, USA
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Silas Maniatis
2Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
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Sanja Vickovic
2Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
3Broad Institute of MIT and Harvard, Cambridge, MA, USA
4Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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Kristy Kang
2Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
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Miguel Cuevas
5Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
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Catherine Braine
2Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
5Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
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Hemali Phatnani
2Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
5Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
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Joakim Lundeberg
4Science for Life Laboratory, Division of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
6Stanford University, Department of Bioengineering, Stanford, CA, USA
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Richard Bonneau
1Center for Computational Biology, Flatiron Institute, New York, NY, USA
7Center for Data Science, New York University, New York, NY, USA
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  • ORCID record for Richard Bonneau
  • For correspondence: rb133@nyu.edu
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Abstract

Spatial genomics technologies enable new approaches to study how cells interact and function in intact multicellular environments but present a host of technical and computational challenges. Here we describe Splotch, a novel computational framework for the analysis of spatially resolved transcriptomics data. Splotch aligns transcriptomics data from multiple tissue sections and timepoints to generate improved posterior estimates of gene expression. We demonstrate alignment of a large corpus of single-cell RNA-seq data into an automatically generated spatial-temporal coordinate and study optimal design for spatial transcriptomics experiments.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted September 05, 2019.
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Splotch: Robust estimation of aligned spatial temporal gene expression data
Tarmo Äijö, Silas Maniatis, Sanja Vickovic, Kristy Kang, Miguel Cuevas, Catherine Braine, Hemali Phatnani, Joakim Lundeberg, Richard Bonneau
bioRxiv 757096; doi: https://doi.org/10.1101/757096
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Splotch: Robust estimation of aligned spatial temporal gene expression data
Tarmo Äijö, Silas Maniatis, Sanja Vickovic, Kristy Kang, Miguel Cuevas, Catherine Braine, Hemali Phatnani, Joakim Lundeberg, Richard Bonneau
bioRxiv 757096; doi: https://doi.org/10.1101/757096

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