RLMM: A Genotype Calling Algorithm for Affymetrix SNP Arrays

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@post.harvard.edu>, Gary Wong <wongg62@berkeley.edu>
Date of publication
None
Maintainer
Nusrat Rabbee <nrabbee@post.harvard.edu>
License
LGPL (>= 2)
Version
1.36.0
URLs

View on Bioconductor

Man pages

Classify
Classification of SNPs based on theta estimates
create_Thetafile
Calculating Parameter Estimates
normalize_Rawfiles
Normalize PM Intensity values
plot_theta
Allele Summary Plot

Files in this package

RLMM/DESCRIPTION
RLMM/NAMESPACE
RLMM/R
RLMM/R/Classify.R
RLMM/R/create_Thetafile.R
RLMM/R/normalize_Rawfiles.R
RLMM/R/plot_theta.R
RLMM/build
RLMM/build/vignette.rds
RLMM/inst
RLMM/inst/doc
RLMM/inst/doc/RLMM.R
RLMM/inst/doc/RLMM.Rnw
RLMM/inst/doc/RLMM.pdf
RLMM/man
RLMM/man/Classify.Rd
RLMM/man/create_Thetafile.Rd
RLMM/man/normalize_Rawfiles.Rd
RLMM/man/plot_theta.Rd
RLMM/vignettes
RLMM/vignettes/RLMM.Rnw
RLMM/vignettes/Xba.rlmm
RLMM/vignettes/Xba.theta
RLMM/vignettes/snps.lst