DOI: 10.18129/B9.bioc.TREG  

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

Bioconductor version: Release (3.17)

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>

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biocViews GeneExpression, RNASeq, Sequencing, SingleCell, Software, Transcription, Transcriptomics
Version 1.4.0
In Bioconductor since BioC 3.15 (R-4.2) (1.5 years)
License Artistic-2.0
Depends R (>= 4.2), SummarizedExperiment
Imports Matrix, purrr, rafalib
Suggests BiocFileCache, BiocStyle, dplyr, ggplot2, knitr, pheatmap, sessioninfo, RefManageR, rmarkdown, testthat (>= 3.0.0), tibble, tidyr, SingleCellExperiment
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