standR

This package is for version 3.20 of Bioconductor; for the stable, up-to-date release version, see standR.

Spatial transcriptome analyses of Nanostring's DSP data in R

Bioconductor version: 3.20

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 iD ORCID: 0000-0002-9487-9305 , Dharmesh D Bhuva [aut] ORCID iD ORCID: 0000-0002-6398-9157 , 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")
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

Need some help? Ask on the Bioconductor Support site!

Details

biocViews DifferentialExpression, ExperimentHubSoftware, GeneExpression, Normalization, QualityControl, Software, Spatial, Transcriptomics

Version 1.10.0

In Bioconductor since BioC 3.15 (R-4.2) (3 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

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Build Report Build Report

Package Archives

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

Source Package standR_1.10.0.tar.gz

Windows Binary (x86_64) standR_1.10.0.zip

macOS Binary (x86_64) standR_1.10.0.tgz

macOS Binary (arm64) standR_1.10.0.tgz

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/

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