To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("RLMM")
In most cases, you don't need to download the package archive at all.
RLMM
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A Genotype Calling Algorithm for Affymetrix SNP Arrays
Bioconductor version: Release (3.5)
A classification algorithm, based on a multi-chip, multi-SNP approach for Affymetrix SNP arrays. Using a large training sample where the genotype labels are known, this aglorithm will obtain more accurate classification results on new data. RLMM is based on a robust, linear model and uses the Mahalanobis distance for classification. The chip-to-chip non-biological variation is removed through normalization. This model-based algorithm captures the similarities across genotype groups and probes, as well as thousands other SNPs for accurate classification. NOTE: 100K-Xba only at for now.
Author: Nusrat Rabbee <nrabbee at post.harvard.edu>, Gary Wong <wongg62 at berkeley.edu>
Maintainer: Nusrat Rabbee <nrabbee at post.harvard.edu>
Citation (from within R,
enter citation("RLMM")):
Installation
To install this package, start R and enter:
## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("RLMM")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RLMM")
| R Script | RLMM Doc | |
| Reference Manual |
Details
| biocViews | GeneticVariability, Microarray, OneChannel, SNP, Software |
| Version | 1.38.0 |
| In Bioconductor since | BioC 1.8 (R-2.3) (11.5 years) |
| License | LGPL (>= 2) |
| Depends | R (>= 2.1.0) |
| Imports | graphics, grDevices, MASS, stats, utils |
| LinkingTo | |
| Suggests | |
| SystemRequirements | Internal files Xba.CQV, Xba.regions (or other regions file) |
| Enhances | |
| URL | http://www.stat.berkeley.edu/users/nrabbee/RLMM |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | RLMM_1.38.0.tar.gz |
| Windows Binary | RLMM_1.38.0.zip |
| Mac OS X 10.11 (El Capitan) | RLMM_1.38.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/RLMM |
| Package Short Url | http://bioconductor.org/packages/RLMM/ |
| Package Downloads Report | Download Stats |
Documentation »
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