SpaceTrooper
SpaceTrooper performs Quality Control analysis of Image-Based spatial
Bioconductor version: 3.23 · Package version: 1.2.0
SpaceTrooper performs Quality Control analysis using data driven GLM models of Image-Based spatial data, providing exploration plots, QC metrics computation, outlier detection. It implements a GLM strategy for the detection of low quality cells in imaging-based spatial data (Transcriptomics and Proteomics). It additionally implements several plots for the visualization of imaging based polygons through the ggplot2 package.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("SpaceTrooper") Details
| Maintainer | Dario Righelli <dario.righelli@gmail.com> |
| Author | Dario Righelli [aut, cre] (ORCID: <https://orcid.org/0000-0003-1504-3583>), Benedetta Banzi [aut], Matteo Marchionni [aut], Oriana Romano [ctb], Mattia Forcato [ctb], Silvio Bicciato [aut], Davide Risso [ctb] |
| License | MIT + file LICENSE |
| URL | https://github.com/drighelli/SpaceTrooper |
| Bug Reports | https://github.com/drighelli/SpaceTrooper/issues |
| Downloads rank | 189 |
| Source branch | RELEASE_3_23 |
| biocViews | DataImport, GeneExpression, ImmunoOncology, QualityControl, SingleCell, Software, Spatial, Transcriptomics |
Documentation
- CosMx Protein Assay Data Quality Control with SpaceTrooper
- Imaging-based Spatial Transcriptomics Data Quality Control with SpaceTrooper
- SpaceTrooper utilities overview
- Loading CosMx and Xenium data with SpaceTrooper
Download
Dependencies
Depends: R (>= 4.4.0), SpatialExperiment
Imports: DropletUtils, S4Vectors, SummarizedExperiment, arrow, data.table, dplyr, e1071, ggplot2, ggpubr, robustbase, scater, scuttle, sf, sfheaders, cowplot, glmnet, rhdf5, methods, rlang, SpatialExperimentIO
Suggests: knitr, rmarkdown, BiocStyle, testthat (>= 3.0.0), withr, viridis