Compute population-level posterior mean variance components

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Last updated: 2021-01-03

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Knit directory: PredictOutbredCrossVar/

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    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk2_AD_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk2_A_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk3_AD_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk3_A_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk4_AD_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk4_A_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk5_AD_predVarsAndCovars.rds
    Deleted:    output/crossPredictions/predUntestedCrosses_top100stdSI_chunk5_A_predVarsAndCovars.rds
    Modified:   output/crossPredictions/predictedCrossMeans.rds
    Modified:   output/crossPredictions/predictedCrossMeans_DirectionalDom_tidy_withSelIndices.rds
    Deleted:    output/crossPredictions/predictedCrossMeans_GCA_SCA.rds
    Modified:   output/crossPredictions/predictedCrossMeans_tidy_withSelIndices.rds
    Modified:   output/crossPredictions/predictedCrossVars_DirectionalDom_tidy_withSelIndices.rds
    Deleted:    output/crossPredictions/predictedCrossVars_GCA_SCA.rds
    Deleted:    output/crossPredictions/predictedCrossVars_chunk1.rds
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    Deleted:    output/crossPredictions/predictedCrossVars_chunk4.rds
    Deleted:    output/crossPredictions/predictedCrossVars_chunk5.rds
    Modified:   output/crossPredictions/predictedCrossVars_tidy_withSelIndices.rds
    Modified:   output/crossPredictions/predictedDirectionalDomCrossMeans.rds
    Deleted:    output/crossPredictions/predictedDirectionalDomCrossVarBVs_chunk1.rds
    Deleted:    output/crossPredictions/predictedDirectionalDomCrossVarBVs_chunk2.rds
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    Deleted:    output/crossPredictions/predictedDirectionalDomCrossVars_chunk5.rds
    Modified:   output/crossPredictions/predictedUntestedCrossMeansBV.rds
    Modified:   output/crossPredictions/predictedUntestedCrossMeansDirDom.rds
    Modified:   output/crossPredictions/predictedUntestedCrossMeansTGV.rds
    Modified:   output/crossPredictions/predictedUntestedCrossMeans_SelIndices.rds
    Modified:   output/crossPredictions/predictedUntestedCrossMeans_tidy_traits.rds
    Modified:   output/crossPredictions/predictedUntestedCrossVars_SelIndices.rds
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    Modified:   output/crossRealizations/realizedCrossMeans.rds
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    Modified:   output/crossRealizations/realizedCrossMetrics.rds
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    Modified:   output/crossRealizations/realized_cross_means_and_covs_traits.rds
    Modified:   output/crossRealizations/realized_cross_means_and_vars_selindices.rds
    Modified:   output/gblups_DirectionalDom_parentwise_crossVal_folds.rds
    Modified:   output/gblups_geneticgroups.rds
    Modified:   output/gblups_parentwise_crossVal_folds.rds
    Modified:   output/gebvs_ModelA_GroupAll_stdSI.rds
    Modified:   output/mtMarkerEffects/mt_All_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold1_testset_DirectionalDom.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold2_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold2_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold2_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold3_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold5_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold5_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold5_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat1_Fold5_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold1_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold1_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold1_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold1_trainset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold2_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold2_trainset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold3_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold3_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold3_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold4_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold5_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold5_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold5_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold5_trainset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat2_Fold5_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold1_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold1_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold1_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold1_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold1_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold2_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold3_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold4_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat3_Fold5_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold1_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold1_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold1_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold1_trainset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold1_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold2_testset_A.rds
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    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold2_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold2_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold2_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold2_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold3_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold4_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat4_Fold5_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold1_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold2_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold3_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold4_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_testset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_testset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_testset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_trainset_A.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_trainset_AD.rds
    Modified:   output/mtMarkerEffects/mt_Repeat5_Fold5_trainset_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_TMS13_A.rds
    Modified:   output/mtMarkerEffects/mt_TMS13_AD.rds
    Modified:   output/mtMarkerEffects/mt_TMS13_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_TMS14_A.rds
    Modified:   output/mtMarkerEffects/mt_TMS14_AD.rds
    Modified:   output/mtMarkerEffects/mt_TMS14_DirectionalDom.rds
    Modified:   output/mtMarkerEffects/mt_TMS15_A.rds
    Modified:   output/mtMarkerEffects/mt_TMS15_AD.rds
    Modified:   output/mtMarkerEffects/mt_TMS15_DirectionalDom.rds
    Modified:   output/obsVSpredMeans.rds
    Modified:   output/obsVSpredUC.rds
    Modified:   output/obsVSpredVars.rds
    Modified:   output/pmv_DirectionalDom_varcomps_geneticgroups.rds
    Modified:   output/pmv_varcomps_geneticgroups.rds
    Modified:   output/pmv_varcomps_geneticgroups_tidy_includingSIvars.rds
    Modified:   workflowr_log.R

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

---

These are the previous versions of the repository in which changes were made to the R Markdown (analysis/getPMVarComps.Rmd) and HTML (docs/getPMVarComps.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File	Version	Author	Date	Message
html	22e6c87	wolfemd	2021-01-03	Build site.
Rmd	ef3f7b3	wolfemd	2021-01-02	Compile submission version of all Rmds with outstanding, uncommitted
Rmd	2e13628	wolfemd	2020-11-25	Misc minor changes
html	3dbb1e8	wolfemd	2020-10-08	Site built for first COMPLETE draft, shared with co-authors.
html	b06eee7	wolfemd	2020-08-31	Build site.
Rmd	576392e	wolfemd	2020-08-27	Commiting all code, output and Rmd as of complete draft of results summaries + figures. Next step is to “assemble” the MS from that.
html	7a4e168	wolfemd	2020-07-31	Build site.
html	a5ac99f	wolfemd	2020-07-31	Build site.
html	ff4fc8b	wolfemd	2020-07-31	Build site.
html	e6f8fe8	wolfemd	2020-07-31	Build site.
Rmd	07509a8	wolfemd	2020-07-31	Organized and ready to be published as a workflowr HTML page.
Rmd	a1950f7	wolfemd	2020-07-29	Directional dominance fully implemented, except in prediction of untested crosses. Presentation to NGC Leader’s call included.
Rmd	c0b292a	wolfemd	2020-06-23	Most analyses coded and complete. Moved all wrapper functions to code/*.R scripts.
Rmd	a6ca472	wolfemd	2020-06-16	Remove analysis to compute PMVs AND subsequent plotting from fitMtBRRs.Rmd to getPMVarComps.Rmd.

---

For each of the genetic groups (GG, C1, C2, C3 , ALL):

Compute the posterior mean variances and covariances from the on-disk-stored, post-burnIn, thinned posterior samples of marker effects.

Models: A, AD, DirDom

For the directional dominance (DirDom) marker effects set. Add inbreeding/propHom effect to vector d.

• Compute \(Var(GEBV)\) with allele sub. effects as: \(\alpha = a + d(q-p)\).
• Compute \(Var(GETGV) = Var(Add) + Var(Dom)\)

Models A and AD

Set-up

# activate multithread OpenBLAS
export OMP_NUM_THREADS=112

rm(list=ls()); gc()
library(tidyverse); library(magrittr); library(predCrossVar); library(BGLR);
blups<-readRDS(here::here("data","blups_forawcdata.rds")) %>% 
  select(Trait,blups) %>% # BLUPs long-->wide for multivar analysis
  unnest(blups) %>% 
  select(Trait,germplasmName,drgBLUP) %>% 
  spread(Trait,drgBLUP) %>%  # choosing de-regressed BLUPs as responses despite unweighted analysis
  select(germplasmName,all_of(c("DM","logFYLD","MCMDS","TCHART"))) # precaution to ensure consistent column order

# SNP data ------------
snps<-readRDS(here::here("data","dosages_awc.rds")) %>% 
  remove_invariant(.); dim(snps) # [1] 5591 38093

# Training datasets -----------
geneticgroups<-blups %>% 
  filter(!grepl("TMS13|TMS14|TMS15",germplasmName)) %>% 
  mutate(Group="GG") %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS13",germplasmName)) %>% 
              mutate(Group="TMS13")) %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS14",germplasmName)) %>% 
              mutate(Group="TMS14")) %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS15",germplasmName)) %>% 
              mutate(Group="TMS15")) %>% 
  bind_rows(blups %>% 
              mutate(Group="All")) %>% 
  nest(blups=-Group) %>% 
  crossing(Model=c("A","AD")) %>% 
  mutate(blups=map(blups,~filter(.,germplasmName %in% rownames(snps))),
         outName=paste0("mt_",Group,"_",Model))

# Parallelization specs ---------
require(furrr); options(future.globals.maxSize=50000*1024^2)
plan(multiprocess); options(mc.cores=10); 

# MCMC params ------
nIter<-30000; burnIn<-5000; thin<-5

# getVarComps function -----------
## Wrapper function for getMultiTraitPMVs_A and getMultiTraitPMVs_AD
## For a given Model / data chunk, load stored posterior marker effects
## Compute vars/covars
source(here::here("code","getVarComps.R"))

Compute var. comps

# cbsulm12 - Done!
geneticgroups %<>% 
  mutate(PMV=future_pmap(.,getVarComps,snps=snps,nIter=30000, burnIn=5000,thin=5))
saveRDS(geneticgroups,file=here::here("output","pmv_varcomps_geneticgroups.rds"))

Model DirDom

Set-up

# activate multithread OpenBLAS
export OMP_NUM_THREADS=112

rm(list=ls()); gc()
library(tidyverse); library(magrittr); library(predCrossVar); library(BGLR);
blups<-readRDS(here::here("data","blups_forawcdata.rds")) %>% 
  select(Trait,blups) %>% # BLUPs long-->wide for multivar analysis
  unnest(blups) %>% 
  select(Trait,germplasmName,drgBLUP) %>% 
  spread(Trait,drgBLUP) %>%  # choosing de-regressed BLUPs as responses despite unweighted analysis
  select(germplasmName,all_of(c("DM","logFYLD","MCMDS","TCHART"))) # precaution to ensure consistent column order

# SNP data ------------
snps<-readRDS(here::here("data","dosages_awc.rds")) %>% 
  remove_invariant(.); dim(snps) # [1] 5591 38093

# Training datasets -----------
geneticgroups<-blups %>% 
  filter(!grepl("TMS13|TMS14|TMS15",germplasmName)) %>% 
  mutate(Group="GG") %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS13",germplasmName)) %>% 
              mutate(Group="TMS13")) %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS14",germplasmName)) %>% 
              mutate(Group="TMS14")) %>% 
  bind_rows(blups %>% 
              filter(grepl("TMS15",germplasmName)) %>% 
              mutate(Group="TMS15")) %>% 
  bind_rows(blups %>% 
              mutate(Group="All")) %>% 
  nest(blups=-Group) %>% 
  crossing(Model=c("DirDomA","DirDomAD")) %>% 
  mutate(blups=map(blups,~filter(.,germplasmName %in% rownames(snps))),
         outName=paste0("mt_",Group,"_DirectionalDom"))

# Parallelization specs ---------
require(furrr); options(future.globals.maxSize=50000*1024^2)
plan(multiprocess); options(mc.cores=10); 

# MCMC params ------
nIter<-30000; burnIn<-5000; thin<-5

# getDirectionalDomVarComps function -----------
## Wrapper function for getMultiTraitPMVs_A and getMultiTraitPMVs_AD
## For a given Model / data chunk, load stored posterior marker effects
## Compute vars/covars
source(here::here("code","getDirectionalDomVarComps.R"))

Compute var. comps

# cbsulm12 - Done!
geneticgroups %<>% 
  mutate(PMV=future_pmap(.,getDirectionalDomVarComps,snps=snps,nIter=30000, burnIn=5000,thin=5))
saveRDS(geneticgroups,file=here::here("output","pmv_DirectionalDom_varcomps_geneticgroups.rds"))

Process results

Tidy VarComps

library(tidyverse); library(magrittr);
geneticgroups<-readRDS(here::here("output","pmv_varcomps_geneticgroups.rds")) %>% 
  bind_rows(readRDS(here::here("output","pmv_DirectionalDom_varcomps_geneticgroups.rds")))
geneticgroups %<>% 
  select(-blups) %>% 
  unnest_wider(PMV) %>% 
  select(-runtime) %>% 
  unnest(pmv) %>% 
  mutate_if(is.numeric,~round(.,6)) %>% 
  pivot_longer(cols=c(VPM,PMV),names_to = "VarMethod",values_to = "Var")

Compute SI variances

# Selection weights -----------
indices<-readRDS(file=here::here("data","selection_index_weights_4traits.rds"))
## Predicted Index Variances
geneticgroups_SI<-geneticgroups %>% 
  nest(varcovars=c(Trait1,Trait2,Var)) %>%
  mutate(varcovars=map(varcovars,
                       function(varcovars){
                         # pairwise to square symmetric matrix
                         gmat<-varcovars %>% 
                           spread(Trait2,Var) %>% 
                           column_to_rownames(var = "Trait1") %>% 
                           as.matrix %>% 
                           .[indices$Trait,indices$Trait]
                         gmat[lower.tri(gmat)]<-t(gmat)[lower.tri(gmat)]
                         return(gmat) }),
         # compute index variances
         stdSI=map_dbl(varcovars,~t(indices$stdSI)%*%.%*%indices$stdSI),
         biofortSI=map_dbl(varcovars,~t(indices$biofortSI)%*%.%*%indices$biofortSI)) %>% 
  # discard var-covar matrix
  select(-varcovars) %>% 
  pivot_longer(cols = c(stdSI,biofortSI),
               names_to = "Trait1", 
               values_to = "Var") %>% 
  mutate(Trait2=Trait1)

geneticgroups %<>% bind_rows(geneticgroups_SI)
rm(geneticgroups_SI)

–> Save

saveRDS(geneticgroups,file=here::here("output","pmv_varcomps_geneticgroups_tidy_includingSIvars.rds"))

Tidy inbreeding effect est. from DirDom model

library(tidyverse); library(magrittr); library(BGLR)
geneticgroups_dd<-readRDS(here::here("output","pmv_DirectionalDom_varcomps_geneticgroups.rds")) %>% 
  distinct(Group,outName) %>% 
  mutate(mtbrrFit=map(outName,~readRDS(here::here("output/mtMarkerEffects",paste0(.,".rds"))))) %>% 
  unnest_wider(mtbrrFit) %>% 
  select(-runtime,-snpIDs,-outName) %>% 
  mutate(Dataset="GeneticGroups")

parentfolds_dd<-readRDS(file = here::here("data","parentwise_crossVal_folds.rds")) %>% 
  rename(Repeat=id,Fold=id2) %>% 
  select(Repeat,Fold,trainset,testset) %>% 
  pivot_longer(c(trainset,testset),
               names_to = "Dataset",
               values_to = "sampleIDs") %>% 
  mutate(Model="DirectionalDom") %>% 
  arrange(desc(Dataset),Repeat,Fold) %>% 
  mutate(outName=paste0("mt_",Repeat,"_",Fold,"_",Dataset,"_",Model)) %>% 
  mutate(mtbrrFit=map(outName,~readRDS(here::here("output/mtMarkerEffects",paste0(.,".rds"))))) %>% 
  unnest_wider(mtbrrFit) %>% 
  select(-runtime,-snpIDs,-sampleIDs,-outName,-Model)
ddEffects<-bind_rows(geneticgroups_dd,parentfolds_dd) %>% 
  mutate(inbreff=map(mtbrrFit,function(mtbrrFit){
    traits<-colnames(mtbrrFit$yHat)
    beta<-mtbrrFit$ETA$GmeanD$beta
    SD.beta<-mtbrrFit$ETA$GmeanD$SD.beta
    colnames(beta)<-colnames(SD.beta)<-traits
    
    inbeffs<-bind_rows(as_tibble(beta),as_tibble(SD.beta)) %>% 
      t(.) %>% 
      as.data.frame %>% 
      rownames_to_column(var="Trait") %>% 
      rename(InbreedingEffect=V1,
             InbreedingEffectSD=V2)
    return(inbeffs) })) %>% 
  select(-mtbrrFit) %>% 
  unnest(inbreff)
saveRDS(ddEffects,file=here::here("output","ddEffects.rds"))

Session information

sessionInfo()

R version 4.0.2 (2020-06-22)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Catalina 10.15.7

Matrix products: default
BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] workflowr_1.6.2

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.5      rstudioapi_0.13 whisker_0.4     knitr_1.30     
 [5] magrittr_2.0.1  R6_2.5.0        rlang_0.4.9     stringr_1.4.0  
 [9] tools_4.0.2     xfun_0.19       git2r_0.27.1    htmltools_0.5.0
[13] ellipsis_0.3.1  rprojroot_2.0.2 yaml_2.2.1      digest_0.6.27  
[17] tibble_3.0.4    lifecycle_0.2.0 crayon_1.3.4    later_1.1.0.1  
[21] vctrs_0.3.5     promises_1.1.1  fs_1.5.0        glue_1.4.2     
[25] evaluate_0.14   rmarkdown_2.6   stringi_1.5.3   compiler_4.0.2 
[29] pillar_1.4.7    httpuv_1.5.4    pkgconfig_2.0.3