Package 'gpcp'

Title: Genomic Prediction of Cross Performance
Description: This function performs genomic prediction of cross performance using genotype and phenotype data. It processes data in several steps including loading necessary software, converting genotype data, processing phenotype data, fitting mixed models, and predicting cross performance based on weighted marker effects. For more information, see Labroo et al. (2023) <doi:10.1007/s00122-023-04377-z>.
Authors: Marlee Labroo [aut], Christine Nyaga [cre, aut], Lukas Mueller [aut]
Maintainer: Christine Nyaga <[email protected]>
License: GPL (>= 3)
Version: 0.1.0
Built: 2024-12-07 07:01:55 UTC
Source: CRAN

Help Index

Example Phenotype Data

Description

This is a sample phenotype dataset used for genomic prediction.

Usage

phenotypeFile

Format

A data frame with 24 columns:

ATW

Description of ATW

AUDPC_YAD

Area Under Disease Progress Curve for YAD

AUDPC_YMV

Area Under Disease Progress Curve for YMV

Accession

Genotype IDs for each individual

Block

Block information

DMC

Dry Matter Content values

Design

Experimental design

LOC

Location of the trials

NPH

Number of Plants Harvested

OXBI

Oxidation Index

Oxint180Minutes

Oxidation intensity after 180 minutes

PLOT

Plot number

REP

Replication number

Settweight

Weight of the planting setts

TTNPL

Total Tuber Number per Plant

TTWPL

Total Tuber Weight per Plant

Trial

Trial name or ID

Vigor

Plant vigor score

YIELD

Yield values

Year

Year of the experiment

Yield.per.plot..kg.

Yield per plot in kilograms

Yield_udj

Unadjusted Yield

rAUDPC_YAD

Relative AUDPC for YAD

rAUDPC_YMV

Relative AUDPC for YMV

Source

Generated for the gpcp package example

Examples

data(phenotypeFile)
head(phenotypeFile)

Genomic Prediction of Cross Performance This function performs genomic prediction of cross performance using genotype and phenotype data.

Description

Genomic Prediction of Cross Performance This function performs genomic prediction of cross performance using genotype and phenotype data.

Usage

runGPCP(
  phenotypeFile,
  genotypeFile,
  genotypes,
  traits,
  weights = NA,
  userSexes = "",
  userFixed = NA,
  userRandom = NA,
  Ploidy = NA,
  NCrosses = NA
)

Arguments

phenotypeFile

A data frame containing phenotypic data, typically read from a CSV file.
genotypeFile

Path to the genotypic data, either in VCF or HapMap format.
genotypes

A character string representing the column name in the phenotype file for the genotype IDs.
traits

A string of comma-separated trait names from the phenotype file.
weights

A numeric vector specifying weights for the traits.
userSexes

A string representing the column name corresponding to the individuals' sexes.
userFixed

A string of comma-separated fixed effect variables.
userRandom

A string of comma-separated random effect variables.
Ploidy

An integer representing the ploidy level of the organism.
NCrosses

An integer specifying the number of top crosses to output.

Value

A data frame containing predicted cross performance.

Examples

# Load phenotype data from CSV
phenotypeFile <- read.csv(system.file("extdata", "phenotypeFile.csv", package = "gpcp"))
genotypeFile <- system.file("extdata", "genotypeFile_Chr9and11.vcf", package = "gpcp")
finalcrosses <- runGPCP(
    phenotypeFile = phenotypeFile,
    genotypeFile = genotypeFile,
    genotypes = "Accession",
    traits = "YIELD,DMC",
    weights = c(3, 1),
    userFixed = "LOC,REP",
    Ploidy = 2,
    NCrosses = 150
)
print(finalcrosses)