MEDME
Modelling Experimental Data from MeDIP Enrichment
Bioconductor version: 2.6
MEDME allows the prediction of absolute and relative methylation levels based on measures obtained by MeDIP-microarray experiments
Author: Mattia Pelizzola and Annette Molinaro
Maintainer: Mattia Pelizzola <mattia.pelizzola at gmail.com>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MEDME")
To cite this package in a publication, start R and enter:
citation("MEDME")
Documentation
| R Script | MEDME.pdf | |
| Reference Manual |
Details
| biocViews | Microarray, CpGIsland |
| Depends | grDevices, graphics, methods, stats, utils |
| Imports | Biostrings, MASS, drc |
| Suggests | BSgenome.Hsapiens.UCSC.hg18, BSgenome.Mmusculus.UCSC.mm9 |
| System Requirements | |
| License | GPL (>= 2) |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.8.0 |
| Since | Bioconductor 2.3 (R-2.8) |
Package Downloads
| Package Source | MEDME_1.8.0.tar.gz |
| Windows Binary | MEDME_1.8.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | MEDME_1.8.0.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
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