The spicyR package provides a framework for performing inference on changes in spatial relationships between pairs of cell types for cell-resolution spatial omics technologies. spicyR consists of thre
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一分鐘完成驗證The spicyR package provides a framework for performing inference on changes in spatial relationships between pairs of cell types for cell-resolution spatial omics technologies. spicyR consists of three primary steps: (i) summarizing the degree of spatial localization between pairs of cell types for each image; (ii) modelling the variability in localization summary statistics as a function of cell counts and (iii) testing for changes in spatial localizations associated with a response variable.
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Test whether cell types co-localise differently between groups of patients.
Do T cells gather around tumour cells more in one group of patients than in another? spicyR tests this for every
pair of cell types in imaging and spatial transcriptomics data, comparing groups of patients or relating
co-localisation to survival. For each image it counts the cells of one type within a radius of each cell of another,
and compares that count with what you would expect if the cells had been labelled at random, using the cells
actually present.檢視完整 README ↗目前無法載入完整 README。請透過原文連結閱讀。 以下為已儲存的摘錄。
Test whether cell types co-localise differently between groups of patients.
Do T cells gather around tumour cells more in one group of patients than in another? spicyR tests this for every
pair of cell types in imaging and spatial transcriptomics data, comparing groups of patients or relating
co-localisation to survival. For each image it counts the cells of one type within a radius of each cell of another,
and compares that count with what you would expect if the cells had been labelled at random, using the cells
actually present.檢視完整 README ↗