DOI: 10.18129/B9.bioc.imcRtools  

This package is for version 3.17 of Bioconductor; for the stable, up-to-date release version, see imcRtools.

Methods for imaging mass cytometry data analysis

Bioconductor version: 3.17

This R package supports the handling and analysis of imaging mass cytometry and other highly multiplexed imaging data. The main functionality includes reading in single-cell data after image segmentation and measurement, data formatting to perform channel spillover correction and a number of spatial analysis approaches. First, cell-cell interactions are detected via spatial graph construction; these graphs can be visualized with cells representing nodes and interactions representing edges. Furthermore, per cell, its direct neighbours are summarized to allow spatial clustering. Per image/grouping level, interactions between types of cells are counted, averaged and compared against random permutations. In that way, types of cells that interact more (attraction) or less (avoidance) frequently than expected by chance are detected.

Author: Nils Eling [aut, cre] , Tobias Hoch [ctb], Vito Zanotelli [ctb], Jana Fischer [ctb], Daniel Schulz [ctb], Lasse Meyer [ctb]

Maintainer: Nils Eling <nils.eling at>

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biocViews Clustering, DataImport, ImmunoOncology, SingleCell, Software, Spatial
Version 1.6.5
In Bioconductor since BioC 3.14 (R-4.1) (2 years)
License GPL-3
Depends R (>= 4.1), SpatialExperiment
Imports S4Vectors, stats, utils, SummarizedExperiment, methods, pheatmap, scuttle, stringr, readr, EBImage, cytomapper, abind, BiocParallel, viridis, dplyr, magrittr, DT, igraph, SingleCellExperiment, vroom, BiocNeighbors, RTriangle, ggraph, tidygraph, ggplot2, data.table, sf, concaveman, tidyselect, distances, MatrixGenerics
Suggests CATALYST, grid, BiocStyle, knitr, rmarkdown, markdown, testthat
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