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multipointR

A package to compare intensities of point patterns across samples with spatial parametric models

Bioconductor version: 3.24 · Package version: 0.99.6

`multipointR` is a package to compare the distribution of cells in an image or cross images with point process models. On a single image level point process models (`ppm`) model the spatial distribution of a cell type point pattern as a function of spatial covariates while accounting for natural spacing of cells. The main model class considered in `multipointR` are inhomgoeneous Gibb's point process models. Across multiple images, users can either compare multiple univariate `ppm` models in a for loop or fit one joint model across all images with `mppm`. `multipointR` provides an interface between `SpatialExperiment` and `SpatialFeatureExperiment` objects and let's users flexibly define their own `ppm`/`mppm` models with R's formula interface.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("multipointR")

Details

MaintainerMartin Emons <martin.emons@uzh.ch>
AuthorMartin Emons [aut, cre] (ORCID: <https://orcid.org/0009-0000-5219-5311>), Wolfgang Huber [aut] (ORCID: <https://orcid.org/0000-0002-0474-2218>), Mark D. Robinson [aut, fnd] (ORCID: <https://orcid.org/0000-0002-3048-5518>)
LicenseGPL (>= 3)
URLhttps://github.com/mjemons/multipointR
Bug Reportshttps://github.com/mjemons/multipointR/issues
Downloads rank23
Source branchdevel
biocViewsSingleCell, Software, Spatial, Transcriptomics

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagemultipointR_0.99.6.tar.gz
Windows binary (x86_64)multipointR_0.99.6.zip
macOS binary (arm64)multipointR_0.99.6.tgz
macOS binary (x86_64)multipointR_0.99.6.tgz
Dependencies

Depends: R (>= 4.1.0)

Imports: SummarizedExperiment, methods, SpatialExperiment, spatstat.geom, spatstat.model, spatstat.explore, formula.tools, mgcv, dplyr, ggplot2, reformulas, S4Vectors, rlang

Suggests: knitr, BiocStyle, patchwork, SpatialFeatureExperiment, rmarkdown, SpatialDatasets, sosta, glmnet, testthat (>= 3.0.0)