- Home
- Bioconductor 2.6
- Software Packages
- OutlierD
OutlierD
Outlier detection using quantile regression on the M-A scatterplots of high-throughput data
Bioconductor version: 2.6
This package detects outliers using quantile regression on the M-A scatterplots of high-throughput data.
Author: HyungJun Cho <hj4cho at korea.ac.kr>
Maintainer: Sukwoo Kim <s4kim at korea.ac.kr>
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("OutlierD")
To cite this package in a publication, start R and enter:
citation("OutlierD")
Documentation
| R Script | Overview | |
| Reference Manual |
Details
| biocViews | Microarray, Bioinformatics |
| Depends | R (>= 2.3.0), Biobase, quantreg |
| Imports | |
| Suggests | |
| System Requirements | |
| License | GPL (>= 2) |
| URL | http://www.korea.ac.kr/~stat2242/ |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Version | 1.12.0 |
| Since | Bioconductor 2.1 (R-2.6) |
Package Downloads
| Package Source | OutlierD_1.12.0.tar.gz |
| Windows Binary | OutlierD_1.12.0.zip (32- & 64-bit) |
| MacOS 10.5 (Leopard) binary | OutlierD_1.12.0.tgz |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Annotation
- Variants
- Flow Cytometry and other assays
Post questions about Bioconductor packages to our mailing lists. Read the posting guide before posting!
Contact us: [email protected]
Hosting provided by Fred Hutchinson Cancer Research Center
Copyright © 2003 - 2012
