Package: RLMM 1.69.0

Nusrat Rabbee

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.

Authors:Nusrat Rabbee <[email protected]>, Gary Wong <[email protected]>

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RLMM.pdf |RLMM.html✨
RLMM/json (API)

# Install 'RLMM' in R:
install.packages('RLMM', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On BioConductor:RLMM-1.69.0(bioc 3.21)RLMM-1.68.0(bioc 3.20)

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

microarrayonechannelsnpgeneticvariability

3.90 score 1 scripts 230 downloads 4 mentions 4 exports 1 dependencies

Last updated 23 days agofrom:b3e0ae7d05. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 31 2024
R-4.5-winNOTEOct 31 2024
R-4.5-linuxNOTEOct 31 2024
R-4.4-winNOTEOct 31 2024
R-4.4-macNOTEOct 31 2024
R-4.3-winNOTEOct 31 2024
R-4.3-macNOTEOct 31 2024

Exports:Classifycreate_Thetafilenormalize_Rawfilesplot_theta

Dependencies:MASS

RLMM Doc

Rendered fromRLMM.Rnwusingutils::Sweaveon Oct 31 2024.

Last update: 2013-11-01
Started: 2013-11-01