Benchmarking cell-type clustering methods for spatially resolved transcriptomics data

Abstract Spatially resolved transcriptomics technologies enable the measurement of transcriptome information while retaining the spatial context at the regional, cellular or sub-cellular level. While previous computational methods have relied on gene expression information alone for clustering singl...

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Bibliographic Details
Published in:	Briefings in bioinformatics Vol. 24; no. 1
Main Authors:	Cheng, Andrew, Hu, Guanyu, Li, Wei Vivian
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 19.01.2023 Oxford Publishing Limited (England)
Subjects:	Accuracy Benchmarking Cluster Analysis Clustering Computer applications Datasets Gene expression Gene Expression Profiling - methods Histology Image enhancement Information retrieval Parameter identification Parameter robustness Population studies Quorum sensing Robustness Software Spatial data Synthetic data Transcriptome Transcriptomes Transcriptomics Clustering Spatial trasncriptomics Single-cell genomics
ISSN:	1467-5463, 1477-4054, 1477-4054
Online Access:	Get full text
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