GLAD
Gain and Loss Analysis of DNA
Bioconductor version: 2.6
Analysis of array CGH data : detection of breakpoints in genomic profiles and assignment of a status (gain, normal or lost) to each chromosomal regions identified.
Author: Philippe Hupe
Maintainer: Philippe Hupe <glad at curie.fr>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("GLAD")
To cite this package in a publication, start R and enter:
citation("GLAD")
Documentation
| R Script | GLAD | |
| Reference Manual |
Details
| biocViews | Microarray, CopyNumberVariants |
| Depends | R (>= 2.5.0) |
| Imports | |
| Suggests | aws, tcltk |
| System Requirements | gsl. Note: users should have GSL installed. Windows users: 'consult the README file available in the inst directory of the source distribution for necessary configuration instructions'. |
| License | GPL |
| URL | http://bioinfo.curie.fr |
| Depends On Me | ITALICS, MANOR |
| Imports Me | MANOR, snapCGH |
| Suggests Me | |
| Version | 2.10.0 |
| Since | Bioconductor 1.6 (R-2.1) or earlier |
Package Downloads
| Package Source | GLAD_2.10.0.tar.gz |
| Windows Binary | GLAD_2.10.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | GLAD_2.10.0.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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