A comprehensive benchmarking with practical guidelines for cellular deconvolution of spatial transcriptomics
King Abdullah University of Science and Technology · Chinese Academy of Sciences · +2 more institutions
Abstract
Spatial transcriptomics technologies are used to profile transcriptomes while preserving spatial information, which enables high-resolution characterization of transcriptional patterns and reconstruction of tissue architecture. Due to the existence of low-resolution spots in recent spatial transcriptomics technologies, uncovering cellular heterogeneity is crucial for disentangling the spatial patterns of cell types, and many related methods have been proposed. Here, we benchmark 18 existing methods resolving a cellular deconvolution task with 50 real-world and simulated datasets by evaluating the accuracy, robustness, and usability of the methods. We compare these methods comprehensively using different…
Citation impact
- FWCI
- 34.60
- Percentile
- 100%
- References
- 39
Authors
10- HLHaoyang LiCorresponding
King Abdullah University of Science and Technology
- JZJuexiao Zhou
King Abdullah University of Science and Technology
- ZLZhongxiao Li
King Abdullah University of Science and Technology
- SCSiyuan Chen
King Abdullah University of Science and Technology
- XLXingyu Liao
King Abdullah University of Science and Technology
Topics & keywords
- Computer science
- Deconvolution
- Benchmarking
- Benchmark (surveying)
- Usability
- Robustness (evolution)
- Spatial analysis
- Data mining
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