A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics

Haoyang Li; Juexiao Zhou; Zhongxiao Li; Siyuan Chen; Xingyu Liao; Bin Zhang; Ruochi Zhang; Yu Wang; Shiwei Sun; Xin Gao

doi:10.1038/s41467-023-37168-7

Nature Communications (Mar 2023)

A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics

Haoyang Li,
Juexiao Zhou,
Zhongxiao Li,
Siyuan Chen,
Xingyu Liao,
Bin Zhang,
Ruochi Zhang,
Yu Wang,
Shiwei Sun,
Xin Gao

Affiliations

Haoyang Li: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Juexiao Zhou: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Zhongxiao Li: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Siyuan Chen: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Xingyu Liao: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Bin Zhang: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)
Ruochi Zhang: Syneron Technology
Yu Wang: Syneron Technology
Shiwei Sun: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences
Xin Gao: Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST)

DOI: https://doi.org/10.1038/s41467-023-37168-7
Journal volume & issue: Vol. 14, no. 1
pp. 1 – 10

Abstract

Read online

This study comprehensively benchmarks 18 state-of-the-art methods for cellular deconvolution of spatial transcriptomics and provide decision-tree-style guidelines and recommendations for method selection.

Published in Nature Communications

ISSN: 2041-1723 (Online)
Publisher: Nature Portfolio
Country of publisher: United Kingdom
LCC subjects: Science
Website: https://www.nature.com/ncomms/

About the journal