SpatialDWLS: Accurate Deconvolution of Spatial Transcriptomic Data

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2021 May 11

PMID 33971932

Citations 123

Authors

Rui Dong

Guo-Cheng Yuan

Affiliations

Soon will be listed here.

Abstract

Recent development of spatial transcriptomic technologies has made it possible to characterize cellular heterogeneity with spatial information. However, the technology often does not have sufficient resolution to distinguish neighboring cell types. Here, we present spatialDWLS, to quantitatively estimate the cell-type composition at each spatial location. We benchmark the performance of spatialDWLS by comparing it with a number of existing deconvolution methods and find that spatialDWLS outperforms the other methods in terms of accuracy and speed. By applying spatialDWLS to a human developmental heart dataset, we observe striking spatial temporal changes of cell-type composition during development.

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