Package: SpaceMarkers 1.1.0

Atul Deshpande

SpaceMarkers: Spatial Interaction Markers

Spatial transcriptomic technologies have helped to resolve the connection between gene expression and the 2D orientation of tissues relative to each other. However, the limited single-cell resolution makes it difficult to highlight the most important molecular interactions in these tissues. SpaceMarkers, R/Bioconductor software, can help to find molecular interactions, by identifying genes associated with latent space interactions in spatial transcriptomics.

Authors:Atul Deshpande [aut, cre], Ludmila Danilova [ctb], Dimitrijs Lvovs [ctb]

SpaceMarkers_1.1.0.tar.gz
SpaceMarkers_1.1.0.zip(r-4.5)SpaceMarkers_1.1.0.zip(r-4.4)SpaceMarkers_1.1.0.zip(r-4.3)
SpaceMarkers_1.1.0.tgz(r-4.4-any)SpaceMarkers_1.1.0.tgz(r-4.3-any)
SpaceMarkers_1.1.0.tar.gz(r-4.5-noble)SpaceMarkers_1.1.0.tar.gz(r-4.4-noble)
SpaceMarkers_1.1.0.tgz(r-4.4-emscripten)SpaceMarkers_1.1.0.tgz(r-4.3-emscripten)
SpaceMarkers.pdf |SpaceMarkers.html✨
SpaceMarkers/json (API)
NEWS

# Install 'SpaceMarkers' in R:

install.packages('SpaceMarkers', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/atuldeshpande/spacemarkers/issues

Datasets:

curated_genes - Curated Genes for example purposes
optParams - Optimal paramters of 5 patterns from CoGAPS.

On BioConductor:SpaceMarkers-1.1.0(bioc 3.20)SpaceMarkers-1.0.0(bioc 3.19)

bioconductor-package

5 exports 1.24 score 77 dependencies

Last updated 2 months agofrom:306f2b7d7e

Exports:getInteractingGenes getSpatialFeatures getSpatialParameters load10XCoords load10XExpr

Dependencies:abind ape backports bit bit64 boot broom car carData cli colorspace corrplot cpp11 deldir digest dplyr fansi farver generics ggplot2 glue goftest gtable hdf5r isoband jsonlite labeling lattice lifecycle lme4 magrittr MASS Matrix MatrixModels matrixStats matrixTests mgcv minqa munsell nlme nloptr nnet numDeriv pbkrtest pillar pkgconfig plyr polyclip purrr quantreg qvalue R6 RColorBrewer Rcpp RcppEigen reshape2 rlang rstatix scales SparseM spatstat.data spatstat.explore spatstat.geom spatstat.random spatstat.sparse spatstat.utils stringi stringr survival tensor tibble tidyr tidyselect utf8 vctrs viridisLite withr

Inferring Immune Interactions in Breast Cancer

Orian Stapleton

Rendered fromSpaceMarkers_vignette.Rmdusingknitr::rmarkdownon Jun 24 2024.

Last update: 2024-03-26
Started: 2024-02-12

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Latent Feature Space for each pattern	cogaps_result
Curated Genes for example purposes	curated_genes
find_genes_of_interest Identify genes associated with pattern interaction. This function identifies genes exhibiting significantly higher values of testMat in the Interaction region of the two patterns compared #' to regions with exclusive influence from either pattern. It uses Kruskal-Wallis test followed by posthoc analysis using Dunn's Test to identify the genes.	find_genes_of_interest
getInteractingGenes Calculate Interaction Regions and Associated Genes This function calculates statistically significant genes using a non-parametric Kruskal-Wallis test for genes in any one region of influence and a post hoc Dunn's test is used for analysis of genes between regions.	getInteractingGenes
getSpatialFeatures Load spatial features	getSpatialFeatures
getSpatialParameters Calculate the Optimal Parameters for Interacting Cells	getSpatialParameters
load10XCoords Load 10x Visium Spatial Coordinates	load10XCoords
load10XExpr load 10X Visium Expression Data	load10XExpr
Optimal paramters of 5 patterns from CoGAPS.	optParams