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mppR: Multi-Parent Population QTL Analysis

Overview

mppR is an R package to perform QTL analysis of experimental multi-parent populations. The population must be composed of crosses between a set of at least three parents (e.g. factorial design, 'diallel', or nested association mapping). The functions cover data processing, QTL detection, and results visualization.

Installation

mppR has two different branches: "master" and "mppR_CRAN". The "master" branch allows to perform MPP mixed model QTL detection calling the asreml-R package and function parent_cluster.mppData that call the archived R package clusthaplo for parent clustering. The branch "mppR_CRAN" do not contain the mixed models and the call to clusthaplo.

devtools::install_github("vincentgarin/mppR", ref = "master")

Usage

See the two vignettes attached to the package.

Travis

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Version

Install

install.packages('mppR')

Monthly Downloads

265

Version

1.4.0

License

GPL-3

Issues

Pull Requests

Stars

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Maintainer

Vincent Garin

Last Published

January 5th, 2023

Functions in mppR (1.4.0)

QTL_gen_effects

QTL genetic effects
inc_mat_QTL

QTL incidence matrix
QTL_forward

Forward regression QTL model
mppData

Complete mppData object
mppData_mdf_pheno

Modify the phenotypic values of a mppData object
mppData_init

mppData object with raw data
mppData_GE

Example mppData object
mppGE_SIM

MPP GxE Simple Interval Mapping
mppGE_CIM

MPP GxE Composite Interval Mapping
mppData_add_pheno

Add new phenotypic values to a mppData object
plot.QTLprof

plot QTL profile
plot_QTLxEC

plot QTLxEC effect
mppGE_proc

MPP GxE QTL analysis
mpp_proc

MPP QTL analysis
mpp_perm

QTL significance threshold by permutation
mpp_CIM

MPP Composite Interval Mapping
par_clu

Parental clustering
parent_cluster.mppData

Parent clustering for mppData objects
mpp_CV

MPP cross-validation
mpp_SIM

MPP Simple Interval Mapping
summary.QeffRes

Summary of QeffRes object
mpp_back_elim

Backward elimination on QTL candidates
summary.mppData

Summary of mppData object
mpp_forward

MPP QTL analysis using forward regression
print.summary.QeffRes

Print summary.QeffRes object
print.summary.mppData

Print summary.mppData object
subset.mppData

Subset mppData object
summary.QR2Res

Summary of QR2Res object
plot_allele_eff_GE

plot of genome wide QTL allelic effect significance
print.summary.QR2Res

Print summary.QR2Res object
MQE_gen_effects

QTL genetic effects multi-QTL effect model
QTL_R2_GE

MPP GxE QTL R2
QTL_R2

QTL global and partial R squared
MQE_proc

Multi-QTL effect MPP analysis
IBS.mppData

IBS coding for mppData objects
IBD.mppData

IBD coding for mppData objects
QTL_effect_GE

MPP GxE QTL genetic effects
QC.mppData

Quality control for mppData objects
CV_partition

Cross validation partition
QTL_effect_QxEC

Estimation of QTL effect sensitivity to environmental covariates
USNAM_map

Reduced map maize US-NAM population
create.mppData

Create a multi-parent population data object
design_connectivity

Connected parts of a MPP design
USNAM_pheno

Reduced phenotype data from Maize US-NAM population
QTL_effect_main_QxE

Estimation of QTL main effect and QTLxE effect
USNAM_geno

Reduced genotype data maize US-NAM population
QTL_select

QTL candidates selection
QTL_pred_R2

Predicted QTL global and partial R squared