DeconRNASeq
Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data
Bioconductor version: Release (3.20)
DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It modeled expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.
Author: Ting Gong <tinggong at gmail.com> Joseph D. Szustakowski <joseph.szustakowski at novartis.com>
Maintainer: Ting Gong <tinggong at gmail.com>
citation("DeconRNASeq")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("DeconRNASeq")
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("DeconRNASeq")
DeconRNASeq Demo | R Script | |
Reference Manual |
Details
biocViews | DifferentialExpression, Software |
Version | 1.48.0 |
In Bioconductor since | BioC 2.11 (R-2.15) (12 years) |
License | GPL-2 |
Depends | R (>= 2.14.0), limSolve, pcaMethods, ggplot2, grid |
Imports | |
System Requirements | |
URL |
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Depends On Me | |
Imports Me | |
Suggests Me | ADAPTS |
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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | DeconRNASeq_1.48.0.tar.gz |
Windows Binary (x86_64) | DeconRNASeq_1.48.0.zip (64-bit only) |
macOS Binary (x86_64) | DeconRNASeq_1.48.0.tgz |
macOS Binary (arm64) | DeconRNASeq_1.47.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/DeconRNASeq |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/DeconRNASeq |
Bioc Package Browser | https://code.bioconductor.org/browse/DeconRNASeq/ |
Package Short Url | https://bioconductor.org/packages/DeconRNASeq/ |
Package Downloads Report | Download Stats |