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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Vydané v:	Briefings in bioinformatics Ročník 24; číslo 1
Hlavní autori:	Cheng, Andrew, Hu, Guanyu, Li, Wei Vivian
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	England Oxford University Press 19.01.2023 Oxford Publishing Limited (England)
Predmet:	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
On-line prístup:	Získať plný text
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