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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DeconRNASeq")
In most cases, you don't need to download the package archive at all.
DeconRNASeq
Deconvolution of Heterogeneous Tissue Samples for mRNA-Seq data
Bioconductor version: 2.14
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 (from within R,
enter citation("DeconRNASeq")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DeconRNASeq")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DeconRNASeq")
| R Script | DeconRNASeq Demo | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, ExperimentData, Software |
| Version | 1.6.0 |
| In Bioconductor since | BioC 2.11 (R-2.15) |
| License | GPL-2 |
| Depends | R (>= 2.14.0), limSolve, pcaMethods, ggplot2, grid |
| Imports | |
| Suggests | |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DeconRNASeq_1.6.0.tar.gz |
| Windows Binary | DeconRNASeq_1.6.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | DeconRNASeq_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | DeconRNASeq_1.6.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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