In miquelvazquez/myphd_ddbb: myphdddbb

### knitr setup
  knitr::opts_chunk$set(echo = TRUE)

### knitr options
  knitr::opts_chunk$set(
    comment = NA,
    fig.path = '01_fig_01_lme4qtl_emmeans_mods.Rmd/',
    fig.width = 20,
    fig.height = 12,
    results = 'markup',
    tidy = FALSE,
    message = FALSE,
    warning = FALSE,
    echo = FALSE)


### options tinytex
  options(tinytex.verbose = FALSE)

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r packages

pacman::p_load(
  devtools, rmarkdown,
  knitr, tinytex, install = TRUE)

### site in 'home'
  setwd(Sys.getenv('HOME'))
  document('~/my_git/myphd_ddbb')
  load_all('~/my_git/myphd_ddbb')

  # load packages
    myphd_ddbb.required_packages()

\newpage

load data

the myphd_ddbb.phen() lists all data for platelet normal population. \newline

### load data
    dat <- myphd_ddbb.phen()


    # list of objects
        l_vars <- myphd_ddbb.traits.platelets()[['original_tr']]
        l_covlist <- myphd_ddbb.covlist_plt.norm()
        all_specs <- c('gr', 'sex', 'gr_sex')       
        l_emmeans <- myphd_ddbb.specs_plt.norm()

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dataset format

### dataset format
  dat[[1]] %>%
   select(ID, starts_with('age'), gr, sex, all_of(head(l_vars, 9)), all_of(tail(l_vars, 2))) %>%
   head(12)

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'lme4qtl' and 'emmeans' models

the myphd_ddbb.l_mods.norm() extract linear mixed models and emmeans models.

\newline

### 'l_mods' & 'l_emmeans'
    l_mods <- suppressMessages(
        myphd_ddbb.l_mods.norm(
            df_mods = dat[[1]],
            df_kinship = dat[[2]],
            vars = l_vars,
            covlist_mods = l_covlist,
            all_specs = all_specs,
            covlist_specs = l_emmeans))