Arabidopsis


The &#145;Arabidopsis&#146; data contains a binary disease-related phenotype of Arabidopsis and an incidence matrix of genotypes from a 250K SNP chip. 


datasets

The package fits large-scale (generalized) ridge regression for various distributions of response. The shrinkage parameters (lambdas) can be pre-specified or estimated using an internal update routine (fitting a heteroscedastic effects model, or HEM). It gives possibility to shrink any subset of parameters in the model. It has special computational advantage for the cases when the number of shrinkage parameters exceeds the number of observations. For example, the package is very useful for fitting large-scale omics data, such as high-throughput genotype data (genomics), gene expression data (transcriptomics), metabolomics data, etc.

Xia Shen

bigRR

Generalized Ridge Regression (with special advantage for p >> n
cases)

Arabidopsis function

The &#145;Arabidopsis&#146; data set contains a phenotype vector <code>y</code> and a genotype matrix <code>Z</code>:
 <dl>
 <dt>y</dt><dd>Binary vector of phenotype AvrRpm1 for 84 inbred lines. See Atwell et al. 2010 Nature for details.</dd> <dt>Z</dt><dd>A 84 times 216100 matrix of genotypes of the 84 inbred lines, with two different homozygotes coded as -1 and 1. 30 SNPs in the original data set that are fixed to only one homozygotic genotype were removed.</dd> </dl>

Format

Atwell, S., Y. S. Huang, B. J. Vilhjalmsson, G. Willems, M. Horton, et al., 2010. Genome-wide association study of 107 phenotypes in Arabidopsis thaliana inbred lines. Nature 465: 627-631.

Arabidopsis: Arabidopsis thaliana data set from Atwell et al. 2010 Nature

Description

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Format

Source

References