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standR

Spatial transcriptome analyses of Nanostring's DSP data in R

Bioconductor version: 3.24 · Package version: 1.17.4

standR is an user-friendly R package providing functions to assist conducting good-practice analysis of Nanostring's GeoMX DSP data. All functions in the package are built based on the SpatialExperiment object, allowing integration into various spatial transcriptomics-related packages from Bioconductor. standR allows data inspection, quality control, normalization, batch correction and evaluation with informative visualizations.

Installation

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

BiocManager::install("standR")

Details

MaintainerNing Liu <ning.liu@adelaide.edu.au>
AuthorNing Liu [aut, cre] (ORCID: <https://orcid.org/0000-0002-9487-9305>), Dharmesh D Bhuva [aut] (ORCID: <https://orcid.org/0000-0002-6398-9157>), Ahmed Mohamed [aut]
LicenseMIT + file LICENSE
URLhttps://github.com/DavisLaboratory/standR
Bug Reportshttps://github.com/DavisLaboratory/standR/issues
Downloads rank544
Source branchdevel
biocViewsDifferentialExpression, ExperimentHubSoftware, GeneExpression, Normalization, QualityControl, Software, Spatial, Transcriptomics

Documentation

Download

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

Source packagestandR_1.17.4.tar.gz
Windows binary (x86_64)standR_1.17.4.zip
macOS binary (arm64)standR_1.17.4.tgz
macOS binary (x86_64)standR_1.17.4.tgz
Dependencies

Depends: R (>= 4.1)

Imports: dplyr, SpatialExperiment (>= 1.5.2), SummarizedExperiment, SingleCellExperiment, edgeR, rlang, rjson, readr, tibble, ggplot2, tidyr, ruv, limma, patchwork, S4Vectors, Biobase, BiocGenerics, grDevices, stats, methods, ggalluvial, mclustcomp, RUVSeq

Suggests: knitr, ExperimentHub, rmarkdown, scater, uwot, ggpubr, ggrepel, cluster, testthat (>= 3.0.0)

Reverse dependencies

Imports Me (1): shinyDSP