design.Z

Function to generate design matrix (Z)

By using 'RAINBOWR' (Reliable Association INference By Optimizing Weights with R), users can test multiple SNPs (Single Nucleotide Polymorphisms) simultaneously by kernel-based (SNP-set) methods. This package can also be applied to haplotype-based GWAS (Genome-Wide Association Study). Users can test not only additive effects but also dominance and epistatic effects. In detail, please check our paper on PLOS Computational Biology: Kosuke Hamazaki and Hiroyoshi Iwata (2020) <doi:10.1371/journal.pcbi.1007663>.

Kosuke Hamazaki

RAINBOWR

Genome-Wide Association Study with SNP-Set Methods

Hiroyoshi Iwata

design.Z function

<dl><dt>pheno.labels</dt>
<dd>A vector of genotype (line; accesion; variety) names which correpond to phenotypic values.</dd>
<dt>geno.names</dt>
<dd>A vector of genotype (line; accesion; variety) names for marker genotype data (duplication is not recommended).</dd></dl>

Arguments

Function to generate design matrix (Z) — design.Z

<dl>

<dt>pheno.labels</dt>
<dd>A vector of genotype (line; accesion; variety) names which correpond to phenotypic values.</dd>


<dt>geno.names</dt>
<dd>A vector of genotype (line; accesion; variety) names for marker genotype data (duplication is not recommended).</dd>

</dl>

design.Z: Function to generate design matrix (Z)

Description

Usage

Value

Arguments