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In Silico Methods for Cell Annotation, Quantification of Gene Expression, and Cell Geometry at Single-Cell Resolution Using 3DCellAtlas.

Methods in molecular biology (Clifton, N.J.) · 1 Jan 2017 · 10.1007/978-1-4939-6469-7_11

Abstract

A comprehensive understanding of plant growth and development requires the integration of the spatial and temporal dynamics of gene regulatory networks with changes in cellular geometry during 3D organ growth. 3DCellAtlas is an integrative computational pipeline that semi-automatically identifies cell type and position within radially symmetric plant organs, and simultaneously quantifies 3D cell anisotropy and reporter abundance at single-cell resolution. It is a powerful tool that generates digital single-cell cellular atlases of plant organs and enables 3D cell geometry and reporter abundance (gene/protein/biosensor) from multiple samples to be integrated at single-cell resolution across whole organs. Here we describe how to use 3DCellAtlas to process and analyze radially symmetric organs, and to identify cell types and extract geometric cell data within these 3D cellular datasets. We detail how to use two statistical tools in 3DCellAtlas to compare cellular geometries, and to analyze reporter abundance at single-cell resolution.

Plant phenotyping relevance

3DCellAtlasは植物器官の細胞形状とレポーター量を単一細胞解像度で抽出・解析する計算パイプラインであり、植物表現型取得手法そのものが中心です。

abstract3DCellAtlas is an integrative computational pipeline that semi-automatically identifies cell type and position within radially symmetric plant organs, and simultaneously quantifies 3D cell anisotropy and reporter abundance at single-cell resolution.
abstractHere we describe how to use 3DCellAtlas to process and analyze radially symmetric organs, and to identify cell types and extract geometric cell data within these 3D cellular datasets.

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