corehunter (version 3.2.3)

corehunter-package: Core Hunter 3

Description

Core Hunter is a tool to sample diverse, representative subsets from large germplasm collections, with minimum redundancy. Such so-called core collections have applications in plant breeding and genetic resource management in general. Core Hunter can construct cores based on genetic marker data, phenotypic traits or precomputed distance matrices, optimizing one of many provided evaluation measures depending on the precise purpose of the core (e.g. maximum diversity, representativeness, or allelic richness). In addition, multiple measures can be simultaneously optimized as part of a weighted index to bring the different perspectives closer together. The Core Hunter library is implemented in Java 8 as an open source project (see http://www.corehunter.org).

Author

Maintainer: Herman De Beukelaer

Authors:

• Guy Davenport

Other contributors:

• Veerle Fack [thesis advisor]

See Also

coreHunterData, genotypes, phenotypes, distances, sampleCore, evaluateCore, objective

Examples

if (FALSE) {
# sample core based on genetic marker data (default format)
geno.file <- system.file("extdata", "genotypes.csv", package = "corehunter")
geno <- genotypes(file = geno.file, format = "default")
core <- sampleCore(geno)

# sample core based on genetic marker data (biparental format)
geno.file <- system.file("extdata", "genotypes-biparental.csv", package = "corehunter")
geno <- genotypes(file = geno.file, format = "biparental")
core <- sampleCore(geno)

# sample core based on genetic marker data (frequency format)
geno.file <- system.file("extdata", "genotypes-frequency.csv", package = "corehunter")
geno <- genotypes(file = geno.file, format = "frequency")
core <- sampleCore(geno)

# sample core based on phenotypic traits
pheno.file <- system.file("extdata", "phenotypes.csv", package = "corehunter")
pheno <- phenotypes(file = pheno.file)
core <- sampleCore(pheno)

# sample core based on precomputed distance matrix
dist.file <- system.file("extdata", "distances.csv", package = "corehunter")
dist <- distances(file = dist.file)
core <- sampleCore(dist)

# sample core from genotypes with custom objective (allelic richness)
core <- sampleCore(geno, obj = objective("HE"))

# sample core from genotypes with custom size and objective (representativeness)
core <- sampleCore(geno, obj = objective("AN", "MR"), size = 0.1)

# sample core from genotypes with custom size and stop condition
core <- sampleCore(geno, size = 0.1, impr.time = 2)

# sample core based on both genotypes and phenotypes
geno.pheno <- coreHunterData(geno, pheno)
core <- sampleCore(geno.pheno)
}