Package: metan 1.18.0

metan: Multi Environment Trials Analysis

Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, geometric adaptability index by Mohammadi & Amri (2008) <doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart & Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method, power law residuals (POLAR) statistics by Doring et al. (2015) <doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <https://link.springer.com/article/10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>. Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.

Authors:Tiago Olivoto [aut, cre, cph]

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NEWS

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

Peer review:

Bug tracker:https://github.com/tiagoolivoto/metan/issues

Datasets:

On CRAN:

ammiammi-modelbiplotsggehmrpgvmgidimtsirpgvstabilitywaaswaasb

10.08 score 35 stars 1 packages 1.2k scripts 2.5k downloads 85 mentions 278 exports 59 dependencies

Last updated 1 months agofrom:cb42576433. Checks:OK: 1 WARNING: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-winWARNINGNov 15 2024
R-4.5-linuxWARNINGNov 15 2024
R-4.4-winWARNINGNov 15 2024
R-4.4-macWARNINGNov 15 2024
R-4.3-winWARNINGNov 15 2024
R-4.3-macWARNINGNov 15 2024

Exports::=.data%>%acvadd_classadd_colsadd_prefixadd_row_idadd_rowsadd_seq_blockadd_suffixall_lower_caseall_pairsall_title_caseall_upper_casealpha_colorammi_indexesAMMI_indexesAnnicchiaricoanova_indanova_jointarrange_ggplotas_characteras_factoras_integeras_labelas_logicalas_nameas_numericas.lpcoras.split_factorsav_devave_devbind_cvblup_indexescan_corrci_mean_tci_mean_zclip_readclip_writeclusteringcoincidence_indexcolindiagcolnames_to_lowercolnames_to_titlecolnames_to_uppercolumn_existscolumn_to_firstcolumn_to_lastcolumn_to_rownamescomb_varsconcatenatecontainscorr_cicorr_coefcorr_focuscorr_plotcorr_sscorr_stab_indcorrelated_varscovcor_designcvcv_ammicv_ammifcv_blupcv_bydesc_statdesc_widerdf_to_selegen_54difference_vardooecovalenceends_withenquoenquosenv_dissimilarityenv_stratificationeverythingextract_numberextract_stringfai_blupfill_nafind_outliersfind_text_in_numfirst_upper_caseFoxfreq_histfreq_tableg_simulagafemgaigamemgamem_metge_acvge_clusterge_detailsge_effectsge_factanalge_meansge_plotge_polarge_regge_simulage_statsge_winnersget_corvarsget_covmatget_distget_level_sizeget_levelsget_levels_combget_model_dataget_wd_hereggeggplot_colorgmdgmeangroup_bygtbgytbhas_classhas_nahas_text_in_numhas_zerohmeanhmgvhmrpgvHuehnimpute_missing_valinspectintersect_varis_balanced_trialis.lpcoris.split_factorskurtlast_collower_case_onlylpcormahalamahala_designmake_longmake_lower_trimake_lower_uppermake_matmake_symmake_upper_trimantel_testmatchesmax_bymean_bymeans_bymgidimin_bympsmtmpsmtsimutaten_byn_missingn_uniquen_validnetwork_plotnon_collinear_varsnum_rangeone_ofopen_wdopen_wd_herepairs_mantelpath_coeffpath_coeff_matpath_coeff_seqperforms_ammiplaisted_petersonplot_barsplot_blupplot_ciplot_eigenplot_factbarsplot_factlinesplot_linesplot_scoresplot_waasbyprogressprop_napseudo_sigmarandom_narange_datarbind_fill_idrecode_factorremove_classremove_colsremove_cols_all_naremove_cols_naremove_cols_zeroremove_rownamesremove_rowsremove_rows_all_naremove_rows_naremove_rows_zeroremove_spaceremove_stringsrenamereorder_colsreorder_cormatreplace_nareplace_numberreplace_stringreplace_zerorescaresidual_plotsresp_surfround_colsrow_col_meanrow_col_sumrownames_to_columnrpgvrun_progresssample_randomsample_systematicSchmildtsd_amosd_bysd_popsel_genselectselect_colsselect_cols_naselect_cols_zeroselect_first_colselect_last_colselect_non_numeric_colsselect_numeric_colsselect_predselect_rowsselect_rows_naselect_rows_zerosemsem_byset_classset_differenceset_intersectset_unionset_wd_hereShuklaskewSmith_Hazelsolve_svdsplit_factorsstars_pvalstarts_withsum_bysum_devsum_sqsum_sq_devsuperioritytheme_metantheme_metan_minimalThennarasutidy_colnamestidy_stringstidy_symtitle_case_onlytransparent_colortranspose_dftukey_hsdunion_varupper_case_onlyvar_amovar_byvar_popvenn_plotwaaswaas_meanswaasbwidth_greater_thanwidth_less_thanwidth_ofwsmp

Dependencies:bootclicolorspacecpp11crayondplyrfansifarverforcatsgenericsGGallyggforceggplot2ggrepelggstatsgluegtablehmsisobandlabelinglatticelifecyclelme4lmerTestmagrittrMASSmathjaxrMatrixmgcvminqamunsellnlmenloptrnumDerivpatchworkpillarpkgconfigplyrpolyclipprettyunitsprogresspurrrR6RColorBrewerRcppRcppEigenrlangscalesstringistringrsystemfontstibbletidyrtidyselecttweenrutf8vctrsviridisLitewithr

Multi-environment Trial Analysis

Tiago Olivoto

Rendered frommetan_start.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2021-11-10
Started: 2020-02-07

Readme and manuals

Help Manual

Help pageTopics
Multi-Environment Trial Analysismetan-package
Adjusted Coefficient of Variationacv
AMMI-based stability indexesAMMI_indexes ammi_indexes
Annicchiarico's genotypic confidence indexAnnicchiarico
Within-environment analysis of varianceanova_ind
Joint analysis of varianceanova_joint
Arrange separate ggplots into the same graphicarrange_ggplot
Coerce to an object of class lpcoras.lpcor
Fast way to create bar plotsbarplots plot_bars plot_factbars
Bind cross-validation objectsbind_cv
Stability indexes based on a mixed-effect modelblup_indexes hmgv hmrpgv rpgv
Canonical correlation analysiscan_corr
Clustering analysisclustering
Computes the coincidence index of genotype selectioncoincidence_index
Collinearity Diagnosticscolindiag
Pairwise combinations of variablescomb_vars
Confidence interval for correlation coefficientcorr_ci
Linear and partial correlation coefficientscorr_coef
Focus on section of a correlation matrixcorr_focus
Visualization of a correlation matrixcorr_plot
Sample size planning for a desired Pearson's correlation confidence intervalcorr_ss
Correlation between stability indexescorr_stab_ind
Generate correlated variablescorrelated_vars
Variance-covariance matrices for designed experimentscovcor_design
Cross-validation procedurecv_ammi
Cross-validation procedurecv_ammif
Cross-validation procedurecv_blup
Data from an alpha lattice designdata_alpha
Single maize trialdata_g
Multi-environment trial of oatdata_ge
Multi-environment trial of maizedata_ge2
Simulate genotype and genotype-environment datadata_simula ge_simula g_simula
Descriptive statisticsdesc_stat desc_wider
Alternative to dplyr::do for doing anythingdoo
Stability analysis based on Wricke's modelecovalence
Dissimilarity between environmentsenv_dissimilarity
Environment stratificationenv_stratification
Multi-trait selection indexfai_blup
Find possible outliers in a datasetfind_outliers
Fox's stability functionFox
Genotype analysis by fixed-effect modelsgafem
Geometric adaptability indexgai
Genotype analysis by mixed-effect modelsgamem
Genotype-environment analysis by mixed-effect modelsgamem_met
Adjusted Coefficient of Variation as yield stability indexge_acv
Cluster genotypes or environmentsge_cluster
Details for genotype-environment trialsge_details
Genotype-environment effectsge_effects
Stability analysis and environment stratificationge_factanal
Genotype-environment meansge_means
Graphical analysis of genotype-vs-environment interactionge_plot
Power Law Residuals as yield stability indexge_polar
Eberhart and Russell's regression modelge_reg
Parametric and non-parametric stability statisticsge_stats
Genotype-environment winnersge_winners
Generate normal, correlated variablesget_corvars
Generate a covariance matrixget_covmat
Get a distance matrixget_dist
Get data from a model easilyget_model_data gmd sel_gen
Genotype plus genotype-by-environment modelgge
Genotype by trait biplotgtb
Genotype by yield*trait biplotgytb
Huehn's stability statisticsHuehn
Missing value imputationimpute_missing_val
Check for common errors in multi-environment trial datainspect
Data for examplesint.effects
Check if a data set is balancedis_balanced_trial
Coerce to an object of class lpcoris.lpcor
Fast way to create line plotslineplots plot_factlines plot_lines
Linear and Partial Correlation Coefficientslpcor
Mahalanobis Distancemahala
Mahalanobis distance from designed experimentsmahala_design
Two-way table to a 'long' formatmake_long
Make a two-way tablemake_mat
Mantel testmantel_test
Data for examplesmeansGxE
Multitrait Genotype-Ideotype Distance Indexmgidi
Mean performance and stability in multi-environment trialsmps
Multi-trait mean performance and stability indexmtmps
Multi-trait stability indexmtsi
Network plot of a correlation matrixnetwork_plot
Select a set of predictors with minimal multicollinearitynon_collinear_vars
Mantel test for a set of correlation matricespairs_mantel
Path coefficients with minimal multicollinearitypath_coeff path_coeff_mat path_coeff_seq
Additive Main effects and Multiplicative Interactionperforms_ammi
Stability analysis based on Plaisted and Peterson (1959)plaisted_peterson
Plot the BLUPs for genotypesplot_blup
Plot the confidence interval for correlationplot_ci
Plot the eigenvaluesplot_eigen
Plot scores in different graphical interpretationsplot_scores
Plot WAASBY values for genotype rankingplot_waasby
Several types of residual plotsplot.anova_joint
Plots an object of class can_corplot.can_cor
Plot an object of class clusteringplot.clustering
Create a correlation heat mapplot.corr_coef
Plot an object of class correlated_varsplot.correlated_vars
Plot the RMSPD of a cross-validation procedureplot.cvalidation
Plot an object of class env_dissimilarityplot.env_dissimilarity
Plot the env_stratification modelplot.env_stratification
Multi-trait selection indexplot.fai_blup
Several types of residual plotsplot.gafem
Several types of residual plotsplot.gamem
Plot an object of class ge_clusterplot.ge_cluster
Plot an object of class ge_effectsplot.ge_effects
Plot the ge_factanal modelplot.ge_factanal
Plot an object of class ge_regplot.ge_reg
Create GGE, GT or GYT biplotsplot.gge
Plot the multi-trait genotype-ideotype distance indexplot.mgidi
Plot the multi-trait stability indexplot.mtmps
Plot the multi-trait stability indexplot.mtsi
Plots an object of class 'path_coeff'plot.path_coeff
Several types of residual plotsplot.performs_ammi
Plot the response surface modelplot.resp_surf
Plot the Smith-Hazel indexplot.sh
Several types of residual plotsplot.waas
Several types of residual plotsplot.waasb
Plot heat maps with genotype rankingplot.wsmp
Predict method for gamem fitspredict.gamem
Predict a two-way table based on GGE modelpredict.gge
Predict the means of a performs_ammi objectpredict.performs_ammi
Predict the means of a waas objectpredict.waas
Predict method for waasb fitspredict.waasb
Print an object of class ammi_indexesprint.ammi_indexes
Print an object of class Annicchiaricoprint.Annicchiarico
Print an object of class anova_indprint.anova_ind
Print an object of class anova_jointprint.anova_joint
Print an object of class can_corprint.can_cor
Print an object of class coincidenceprint.coincidence
Print an object of class colindiagprint.colindiag
Print an object of class corr_coefprint.corr_coef
Print an object of class ecovalenceprint.ecovalence
Print an object of class env_dissimilarityprint.env_dissimilarity
Print the env_stratification modelprint.env_stratification
Print an object of class Foxprint.Fox
Print an object of class gamemprint.gamem
Print an object of class ge_factanalprint.ge_factanal
Print an object of class ge_regprint.ge_reg
Print an object of class ge_statsprint.ge_stats
Print an object ofclass 'Huehn'print.Huehn
Print the partial correlation coefficientsprint.lpcor
Print an object of class mgidi Print a 'mgidi' object in two ways. By default, the results are shown in the R console. The results can also be exported to the directory.print.mgidi
Print an object of class mtmpsprint.mtmps
Print an object of class mtsiprint.mtsi
Print an object of class path_coeffprint.path_coeff
Print an object of class performs_ammiprint.performs_ammi
Print an object of class plaisted_petersonprint.plaisted_peterson
Print an object of class Schmildtprint.Schmildt
Print an object of class shprint.sh
Print an object of class Shuklaprint.Shukla
Print an object ofclass 'superiority'print.superiority
Print an object ofclass 'Thennarasu'print.Thennarasu
Print an object of class waasprint.waas
Print an object of class waas_meansprint.waas_means
Print an object of class waasbprint.waasb
Reorder a correlation matrixreorder_cormat
Rescale a variable to have specified minimum and maximum valuesresca
Several types of residual plotsresidual_plots
Response surface modelresp_surf
Schmildt's genotypic confidence indexSchmildt
Select helperdifference_var intersect_var lower_case_only Select_helper title_case_only union_var upper_case_only width_greater_than width_less_than width_of
Selects a best subset of predictor variables.select_pred
Shukla's stability variance parameterShukla
Smith-Hazel indexSmith_Hazel
Pseudoinverse of a square matrixsolve_svd
Split a data frame by factorsas.split_factors is.split_factors split_factors
Generate significance stars from p-valuesstars_pval
Lin e Binns' superiority indexsuperiority
Personalized theme for ggplot2-based graphicsalpha_color ggplot_color themes theme_metan theme_metan_minimal transparent_color
Thennarasu's stability statisticsThennarasu
Transpose a data frametranspose_df
Tukey Honest Significant Differencestukey_hsd
Encode variables to a specific formatas_character as_factor as_integer as_logical as_numeric utils_as
Helper function for binding rowsrbind_fill_id utils_bind
Utilities for handling with classesadd_class has_class remove_class set_class utils_class
Utilities for data Copy-Pastaclip_read clip_write utils_data
Utilities for data organizationadd_seq_block df_to_selegen_54 recode_factor utils_data_org
Utilities for handling with matricesmake_lower_tri make_lower_upper make_sym make_upper_tri tidy_sym utils_mat
Utilities for handling with NA and zero valuesfill_na has_na has_zero prop_na random_na remove_cols_all_na remove_cols_na remove_cols_zero remove_rows_all_na remove_rows_na remove_rows_zero replace_na replace_zero select_cols_na select_cols_zero select_rows_na select_rows_zero utils_na_zero
Utilities for handling with numbers and stringsall_lower_case all_title_case all_upper_case extract_number extract_string find_text_in_num first_upper_case has_text_in_num remove_space remove_strings replace_number replace_string round_cols tidy_strings utils_num_str
Utilities for text progress bar in the terminalprogress run_progress utils_progress
Utilities for handling with rows and columnsadd_cols add_prefix add_rows add_row_id add_suffix all_pairs colnames_to_lower colnames_to_title colnames_to_upper column_exists column_to_first column_to_last column_to_rownames concatenate get_levels get_levels_comb get_level_size remove_cols remove_rownames remove_rows reorder_cols rownames_to_column select_cols select_first_col select_last_col select_non_numeric_cols select_numeric_cols select_rows tidy_colnames utils_rows_cols
Random Samplingsample_random sample_systematic utils_samples
Utilities for set operations for many setsset_difference set_intersect set_union utils_sets
Useful functions for computing descriptive statisticsave_dev av_dev ci_mean_t ci_mean_z cv cv_by freq_hist freq_table gmean hmean kurt max_by means_by mean_by min_by n_by n_missing n_unique n_valid pseudo_sigma range_data row_col_mean row_col_sum sd_amo sd_by sd_pop sem sem_by skew sum_by sum_dev sum_sq sum_sq_dev utils_stats var_amo var_by var_pop
Set and get the Working Directory quickyget_wd_here open_wd open_wd_here set_wd_here utils_wd
Draw Venn diagramsvenn_plot
Weighted Average of Absolute Scoreswaas
Weighted Average of Absolute Scoreswaas_means
Weighted Average of Absolute Scoreswaasb
Weighting between stability and mean performancewsmp