RLMM

This is the development version of RLMM; for the stable release version, see RLMM.

A Genotype Calling Algorithm for Affymetrix SNP Arrays


Bioconductor version: Development (3.21)

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 (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("RLMM")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("RLMM")
RLMM Doc PDF R Script
Reference Manual PDF

Details

biocViews GeneticVariability, Microarray, OneChannel, SNP, Software
Version 1.69.0
In Bioconductor since BioC 1.8 (R-2.3) (18.5 years)
License LGPL (>= 2)
Depends R (>= 2.1.0)
Imports graphics, grDevices, MASS, stats, utils
System Requirements Internal files Xba.CQV, Xba.regions (or other regions file)
URL http://www.stat.berkeley.edu/users/nrabbee/RLMM
See More
Suggests
Linking To
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package RLMM_1.69.0.tar.gz
Windows Binary (x86_64) RLMM_1.69.0.zip (64-bit only)
macOS Binary (x86_64) RLMM_1.69.0.tgz
macOS Binary (arm64) RLMM_1.69.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/RLMM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/RLMM
Bioc Package Browser https://code.bioconductor.org/browse/RLMM/
Package Short Url https://bioconductor.org/packages/RLMM/
Package Downloads Report Download Stats