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Giotto: a toolbox for integrative analysis and visualization of spatial expression data

Authors :
Ruben Dries
Qian Zhu
Rui Dong
Chee-Huat Linus Eng
Huipeng Li
Kan Liu
Yuntian Fu
Tianxiao Zhao
Arpan Sarkar
Feng Bao
Rani E. George
Nico Pierson
Long Cai
Guo-Cheng Yuan
Source :
Genome Biology, Vol 22, Iss 1, Pp 1-31 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.

Details

Language :
English
ISSN :
1474760X
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.4e88a78b4f8948f69e0ebf5aa8ff65bc
Document Type :
article
Full Text :
https://doi.org/10.1186/s13059-021-02286-2