Package: mppR 1.5.0

mppR: Multi-Parent Population QTL Analysis

Analysis of experimental multi-parent populations to detect regions of the genome (called quantitative trait loci, QTLs) influencing phenotypic traits measured in unique and multiple environments. 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. The implemented methodology is described in Garin, Wimmer, Mezmouk, Malosetti and van Eeuwijk (2017) <doi:10.1007/s00122-017-2923-3>, in Garin, Malosetti and van Eeuwijk (2020) <doi:10.1007/s00122-020-03621-0>, and in Garin, Diallo, Tekete, Thera, ..., and Rami (2024) <doi:10.1093/genetics/iyae003>.

Authors:Vincent Garin [aut, cre], Valentin Wimmer [aut], Dietrich Borchardt [ctb, dtc], Fred van Eeuwijk [ctb, ths], Marcos Malosetti [ctb, ths]

mppR_1.5.0.tar.gz
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mppR_1.5.0.tgz(r-4.4-any)mppR_1.5.0.tgz(r-4.3-any)
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mppR.pdf |mppR.html✨
mppR/json (API)
NEWS

# Install 'mppR' in R:
install.packages('mppR', repos = c('https://vincentgarin.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/vincentgarin/mppr/issues

Datasets:

On CRAN:

5.65 score 2 stars 28 scripts 226 downloads 4 mentions 34 exports 34 dependencies

Last updated 9 months agofrom:02e4672561. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-winOKNov 06 2024
R-4.5-linuxOKNov 06 2024
R-4.4-winOKNov 06 2024
R-4.4-macOKNov 06 2024
R-4.3-winOKNov 06 2024
R-4.3-macOKNov 06 2024

Exports:create.mppDataCV_partitiondesign_connectivityEC_effectIBD.mppDataIBS.mppDatainc_mat_QTLmpp_back_elimmpp_CIMmpp_CVmpp_forwardmpp_permmpp_procmpp_SIMmppData_add_phenomppData_mdf_phenomppGE_CIMmppGE_procmppGE_SIMMQE_gen_effectsMQE_procparent_cluster.mppDataplot_allele_eff_GEplot_QxECQC.mppDataQTL_effect_GEQTL_effect_main_QEIQTL_effect_main_QxECQTL_forwardQTL_gen_effectsQTL_pred_R2QTL_R2QTL_R2_GEQTL_select

Dependencies:clicolorspacecpp11dplyrfansifarvergenericsggplot2gluegtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigqtlR6RColorBrewerrlangscalestibbletidyselectutf8vctrsviridisLitewithr

mppR: An R Package for QTL Analysis in Multi-parent Populations

Vincent Garin^[Wageningen University, [email protected]], Valentin Wimmer^[KWS SAAT SE], Dietriech Borchardt^[KWS SAAT SE], Fred van Eeuwijk^[Wageningen University], Marcos Malosetti^[Wageningen University]

Rendered frommppR_gen_vignette.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2023-01-03
Started: 2023-01-03

QTL detection in multiparental populations characterized in multiple environments

Vincent Garin

Rendered fromMPP_ME_QTL_detect.Rmdusingknitr::rmarkdownon Nov 06 2024.

Last update: 2024-02-22
Started: 2023-01-03

Readme and manuals

Help Manual

Help pageTopics
Create a multi-parent population data objectcreate.mppData
Cross validation partitionCV_partition
Connected parts of a MPP designdesign_connectivity
Determine EC effectsEC_effect
IBD coding for 'mppData' objectsIBD.mppData
IBS coding for 'mppData' objectsIBS.mppData
QTL incidence matrixinc_mat_QTL
Backward elimination on QTL candidatesmpp_back_elim
MPP Composite Interval Mappingmpp_CIM
MPP cross-validationmpp_CV
MPP QTL analysis using forward regressionmpp_forward
QTL significance threshold by permutationmpp_perm
MPP QTL analysismpp_proc
MPP Simple Interval Mappingmpp_SIM
Complete 'mppData' objectmppData
Add new phenotypic values to a mppData objectmppData_add_pheno
Example 'mppData' objectmppData_GE
'mppData' object with raw datamppData_init
Modify the phenotypic values of a mppData objectmppData_mdf_pheno
MPP GxE Composite Interval MappingmppGE_CIM
MPP GxE QTL analysismppGE_proc
MPP GxE Simple Interval MappingmppGE_SIM
QTL genetic effects multi-QTL effect modelMQE_gen_effects
Multi-QTL effect MPP analysisMQE_proc
Parental clusteringpar_clu
Parent clustering for 'mppData' objectsparent_cluster.mppData
plot of genome wide QTL allelic effect significanceplot_allele_eff_GE
plot QTLxEC effectplot_QxEC
plot QTL profileplot.QTLprof
Print summary.mppData objectprint.summary.mppData
Print summary.QeffRes objectprint.summary.QeffRes
Print summary.QR2Res objectprint.summary.QR2Res
Quality control for 'mppData' objectsQC.mppData
MPP GxE QTL genetic effectsQTL_effect_GE
Main and QTL by environment interaction modelQTL_effect_main_QEI
Estimation of a model with main and QTL by environmental sensitivity termsQTL_effect_main_QxEC
Forward regression QTL modelQTL_forward
QTL genetic effectsQTL_gen_effects
Predicted QTL global and partial R squaredQTL_pred_R2
QTL global and partial R squaredQTL_R2
MPP GxE QTL R2QTL_R2_GE
QTL candidates selectionQTL_select
Subset 'mppData' objectsubset.mppData
Summary of 'mppData' objectsummary.mppData
Summary of 'QeffRes' objectsummary.QeffRes
Summary of 'QR2Res' objectsummary.QR2Res
Reduced genotype data maize US-NAM populationUSNAM_geno
Reduced map maize US-NAM populationUSNAM_map
Reduced phenotype data from Maize US-NAM populationUSNAM_pheno