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TREG

Tools for finding Total RNA Expression Genes in single nucleus RNA-seq data


Bioconductor version: Release (3.18)

RNA abundance and cell size parameters could improve RNA-seq deconvolution algorithms to more accurately estimate cell type proportions given the different cell type transcription activity levels. A Total RNA Expression Gene (TREG) can facilitate estimating total RNA content using single molecule fluorescent in situ hybridization (smFISH). We developed a data-driven approach using a measure of expression invariance to find candidate TREGs in postmortem human brain single nucleus RNA-seq. This R package implements the method for identifying candidate TREGs from snRNA-seq data.

Author: Louise Huuki-Myers [aut, cre] , Leonardo Collado-Torres [ctb]

Maintainer: Louise Huuki-Myers <lahuuki at gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("TREG")

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("TREG")
How to find Total RNA Expression Genes (TREGs) HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcription, Transcriptomics
Version 1.6.0
In Bioconductor since BioC 3.15 (R-4.2) (2 years)
License Artistic-2.0
Depends R (>= 4.2), SummarizedExperiment
Imports Matrix, purrr, rafalib
System Requirements
URL https://github.com/LieberInstitute/TREG http://research.libd.org/TREG/
Bug Reports https://support.bioconductor.org/t/TREG
See More
Suggests BiocFileCache, BiocStyle, dplyr, ggplot2, knitr, pheatmap, sessioninfo, RefManageR, rmarkdown, testthat (>= 3.0.0), tibble, tidyr, SingleCellExperiment
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 TREG_1.6.0.tar.gz
Windows Binary TREG_1.6.0.zip (64-bit only)
macOS Binary (x86_64) TREG_1.6.0.tgz
macOS Binary (arm64) TREG_1.6.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/TREG
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/TREG
Bioc Package Browser https://code.bioconductor.org/browse/TREG/
Package Short Url https://bioconductor.org/packages/TREG/
Package Downloads Report Download Stats