standR

This is the development version of standR; for the stable release version, see standR.

Spatial transcriptome analyses of Nanostring's DSP data in R


Bioconductor version: Development (3.21)

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.

Author: Ning Liu [aut, cre] (ORCID: ), Dharmesh D Bhuva [aut] (ORCID: ), Ahmed Mohamed [aut]

Maintainer: Ning Liu <liu.n at wehi.edu.au>

Citation (from within R, enter citation("standR")):

Installation

To install this package, start R (version "4.5") and enter:


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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("standR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("standR")
standR_introduction HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews DifferentialExpression, ExperimentHubSoftware, GeneExpression, Normalization, QualityControl, Software, Spatial, Transcriptomics
Version 1.11.0
In Bioconductor since BioC 3.15 (R-4.2) (2.5 years)
License MIT + file LICENSE
Depends R (>= 4.1)
Imports dplyr, SpatialExperiment(>= 1.5.2), SummarizedExperiment, SingleCellExperiment, edgeR, rlang, readr, tibble, ggplot2, tidyr, ruv, limma, patchwork, S4Vectors, Biobase, BiocGenerics, grDevices, stats, methods, ggalluvial, mclustcomp, RUVSeq
System Requirements
URL https://github.com/DavisLaboratory/standR
Bug Reports https://github.com/DavisLaboratory/standR/issues
See More
Suggests knitr, ExperimentHub, rmarkdown, scater, uwot, ggpubr, ggrepel, cluster, testthat (>= 3.0.0)
Linking To
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package standR_1.11.0.tar.gz
Windows Binary (x86_64) standR_1.11.0.zip
macOS Binary (x86_64) standR_1.11.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/standR
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/standR
Bioc Package Browser https://code.bioconductor.org/browse/standR/
Package Short Url https://bioconductor.org/packages/standR/
Package Downloads Report Download Stats