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Dose-response-assay-plots.md

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Dose response assay plots

Emily J Tallerday 2023-06-30

Setup

Load packages to be used

packages <- c("rmarkdown", "pandoc", "formatR", "tidyverse", "gridExtra", "ggpubr", "viridis", "ggthemes", "here", "gplots", "cowplot", "ggtext", "ggsignif", "ggokabeito")
pacman::p_load(char = packages, install = T, character.only = T)

Set ggplot theme

My personal preference:

theme_set(theme_light())

Define functions

This section may be empty if functions are not needed.

Data

Import

BA_response <- read.csv(here(r"(Data\06292023_Eva_BA response data.csv)"))

NOTE that this data was provided by Eva from a magenta box BA dose response assay done in Summer 2023.

Tidy data for easy working

BA_response$treatment[BA_response$treatment == "veh"] <- 0
BA_response$genotype <- as.factor(BA_response$genotype)
BA_response$treatment <- as.numeric(BA_response$treatment)
colnames(BA_response) <- c("Genotype", "Conc. BA (ng/uL)", "Shoot length (cm)", "Root length (cm)")

Plot

Linear regression

The code for the following plot was modified from this tutorial by datanovia.

BA_response %>%
  ggplot(aes(x = `Conc. BA (ng/uL)`, y = `Root length (cm)`, color = Genotype, fill = Genotype)) +
  geom_point(shape = 21, size = 2, alpha = 0.5, color = "black") +
  geom_smooth(method = "lm", se = T, alpha = 0.2) +
  facet_wrap(~Genotype,
    ncol = 4,
    nrow = 1,
    scales = "free"
  ) +
  theme(strip.background = element_blank()) +
  stat_regline_equation(color = "black") +
  labs(
    color = "Genotype",
    fill = "Genotype"
  ) +
  scale_color_okabe_ito() +
  scale_fill_okabe_ito()

Session info

sessionInfo()
## R version 4.2.2 (2022-10-31 ucrt)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 22621)
## 
## Matrix products: default
## 
## locale:
## [1] LC_COLLATE=English_United States.utf8 
## [2] LC_CTYPE=English_United States.utf8   
## [3] LC_MONETARY=English_United States.utf8
## [4] LC_NUMERIC=C                          
## [5] LC_TIME=English_United States.utf8    
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] ggokabeito_0.1.0  ggsignif_0.6.4    ggtext_0.1.2      cowplot_1.1.1    
##  [5] gplots_3.1.3      here_1.0.1        ggthemes_4.2.4    viridis_0.6.3    
##  [9] viridisLite_0.4.2 ggpubr_0.6.0      gridExtra_2.3     lubridate_1.9.2  
## [13] forcats_1.0.0     stringr_1.5.0     dplyr_1.1.2       purrr_1.0.1      
## [17] readr_2.1.4       tidyr_1.3.0       tibble_3.2.1      ggplot2_3.4.2    
## [21] tidyverse_2.0.0   formatR_1.14      pandoc_0.1.0      rmarkdown_2.22   
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.10        lattice_0.20-45    gtools_3.9.4       rprojroot_2.0.3   
##  [5] digest_0.6.32      utf8_1.2.3         R6_2.5.1           backports_1.4.1   
##  [9] evaluate_0.21      highr_0.10         pillar_1.9.0       rlang_1.1.1       
## [13] rstudioapi_0.14    car_3.1-2          Matrix_1.5-4.1     labeling_0.4.2    
## [17] splines_4.2.2      polynom_1.4-1      munsell_0.5.0      gridtext_0.1.5    
## [21] broom_1.0.5        compiler_4.2.2     xfun_0.39          pkgconfig_2.0.3   
## [25] mgcv_1.8-41        htmltools_0.5.5    tidyselect_1.2.0   fansi_1.0.4       
## [29] tzdb_0.4.0         withr_2.5.0        bitops_1.0-7       rappdirs_0.3.3    
## [33] grid_4.2.2         nlme_3.1-160       gtable_0.3.3       lifecycle_1.0.3   
## [37] pacman_0.5.1       magrittr_2.0.3     scales_1.2.1       KernSmooth_2.23-20
## [41] cli_3.6.1          stringi_1.7.12     carData_3.0-5      farver_2.1.1      
## [45] fs_1.6.2           xml2_1.3.4         generics_0.1.3     vctrs_0.6.3       
## [49] tools_4.2.2        glue_1.6.2         hms_1.1.3          abind_1.4-5       
## [53] fastmap_1.1.1      yaml_2.3.7         timechange_0.2.0   colorspace_2.1-0  
## [57] caTools_1.18.2     rstatix_0.7.2      knitr_1.43