### 1B - repellent screen:
plan <- drake::drake_plan(
library(tidyverse),
library(patchwork),
#filepath = here::here("data/Figure1B_avoidance.csv"),
screen_data = read.csv(drake::file_in(here::here("data/Figure1B_avoidance.csv"))) %>%
filter(assay %in% c('oct', 'nonanone')) %>%
format_CIdata() %>% mutate(strain = fct_relevel(strain, 'OP50')),
meanOP50 = screen_data %>%
dplyr::filter(strain == 'OP50') %>%
group_by(assay) %>%
summarise(meanLogit = mean(logit.p)),
# mean_nonanone = dplyr::filter(meanOP50, assay == 'nonanone') %>% dplyr::select(meanLogit) %>% as.numeric(),
# mean_octanol = dplyr::filter(meanOP50, assay == 'oct') %>% dplyr::select(meanLogit) %>% as.numeric(),
nonanone_data = screen_data %>%
dplyr::filter(assay == 'nonanone') %>%
mutate(rel.Logit = logit.p - mean(dplyr::filter(., strain == 'OP50')$logit.p)),
octanol_data = screen_data %>%
dplyr::filter(assay == 'oct') %>%
mutate(rel.Logit = logit.p - mean(dplyr::filter(., strain == 'OP50')$logit.p)),
plotColors = c('#827E7E','#C93030', '#2F8A34','#484CC7','#B8B1B1', '#E6DDDD', 'gray94'),
plot1 = nonanone_data %>% dplyr::filter(genotype == 'N2') %>%
plot_plasticityIndex(xvar = strain,
plotColors = c('#827E7E','#C93030', '#2F8A34','#484CC7','#B8B1B1', '#E6DDDD', 'gray94')) +
guides(fill = FALSE),
plot2 = octanol_data %>% dplyr::filter(genotype == 'N2') %>%
plot_plasticityIndex(xvar = strain,
plotColors = c('#827E7E','#C93030', '#2F8A34','#484CC7','#B8B1B1', '#E6DDDD', 'gray94')),
repellents = plot1 + plot2
)
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