To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DTA")
In most cases, you don't need to download the package archive at all.
DTA
Dynamic Transcriptome Analysis
Bioconductor version: 3.0
Dynamic Transcriptome Analysis (DTA) can monitor the cellular response to perturbations with higher sensitivity and temporal resolution than standard transcriptomics. The package implements the underlying kinetic modeling approach capable of the precise determination of synthesis- and decay rates from individual microarray or RNAseq measurements.
Author: Bjoern Schwalb, Benedikt Zacher, Sebastian Duemcke, Achim Tresch
Maintainer: Bjoern Schwalb <schwalb at lmb.uni-muenchen.de>
Citation (from within R,
enter citation("DTA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("DTA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DTA")
| R Script | A guide to Dynamic Transcriptome Analysis (DTA) | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, GeneExpression, Microarray, Software, Transcription |
| Version | 2.12.1 |
| In Bioconductor since | BioC 2.9 (R-2.14) |
| License | Artistic-2.0 |
| Depends | R (>= 2.10), LSD |
| Imports | scatterplot3d |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | DTA_2.12.1.tar.gz |
| Windows Binary | DTA_2.12.1.zip |
| Mac OS X 10.6 (Snow Leopard) | DTA_2.12.1.tgz |
| Mac OS X 10.9 (Mavericks) | DTA_2.12.1.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
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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