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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("mitoODEdata")
In most cases, you don't need to download the package archive at all.
mitoODEdata
Experimental data associated to the paper "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" (submitted).
Bioconductor version: 3.0
This package contains the experimental data (assay annotation, siRNA annotation, time-lapse cell counts) associated to the paper "Dynamical modelling of phenotypes in a genome-wide RNAi live-cell imaging assay" (submitted). The data ultimately come from the Mitocheck assay reported in "Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes" (Neumann, Walter et al, Nature 2010).
Author: Gregoire Pau
Maintainer: Gregoire Pau <pau.gregoire at gene.com>
Citation (from within R,
enter citation("mitoODEdata")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("mitoODEdata")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("mitoODEdata")
| R Script | Mitoode data | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | CellBasedAssays, ExperimentData, Preprocessing, TimeCourse |
| Version | 1.1.1 |
| License | LGPL |
| Depends | R (>= 2.14.0) |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | mitoODE |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | mitoODEdata_1.1.1.tar.gz |
| Windows Binary | mitoODEdata_1.1.1.zip |
| Mac OS X 10.6 (Snow Leopard) | mitoODEdata_1.1.1.tgz |
| Mac OS X 10.9 (Mavericks) | mitoODEdata_1.1.1.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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