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 (3.19)

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] , Dharmesh D Bhuva [aut] , 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 "4.4") 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


Reference Manual	PDF

Need some help? Ask on the Bioconductor Support site!

Details

biocViews	DifferentialExpression, ExperimentHubSoftware, GeneExpression, Normalization, QualityControl, Software, Spatial, Transcriptomics
Version	1.7.4
In Bioconductor since	BioC 3.15 (R-4.2) (2 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

Suggests	knitr, ExperimentHub, rmarkdown, scater, uwot, ggpubr, ggrepel, cluster, testthat (>= 3.0.0)
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report	Build Report

Package Archives

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

Source Package
Windows Binary
macOS Binary (x86_64)
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
Package Short Url	https://bioconductor.org/packages/standR/
Package Downloads Report	Download Stats