octr1_Ps <- MF.matR::plotGCaMP_multi(FileFilter = "Ps", gentoype = octr1, center_on_pulse = "ON", cue = octanol, food = Ps, show.plots = FALSE)
octr1_OP <- MF.matR::plotGCaMP_multi(FileFilter = "OP50", gentoype = octr1, center_on_pulse = "ON", cue = octanol, food = OP50, show.plots = FALSE)
octr1 <- rbind(octr1_OP$data,octr1_Ps$data) %>% unnest %>% group_by(food, animal, animal_num, maxD) %>%
nest()
octr1 %>% unnest() %>% group_by(animal, animal_num, food, maxD) %>%
nest() %>% ggplot(aes(x = food, y = maxD)) + ggbeeswarm::geom_quasirandom(width = 0.2) +
ProvidenciaChemo::add.mean("maxD") +
ProvidenciaChemo::add.quartiles("maxD") +
ProvidenciaChemo::theme_my_ppt +
ProvidenciaChemo::figure.axes()
octr1 %>% unnest() %>% group_by(animal, animal_num, food, maxD) %>%
nest() %$% wilcox.test(maxD ~ food)
octr1_OP$plot + ProvidenciaChemo::theme_my_ppt
N2_Ps <- MF.matR::plotGCaMP_multi(genotype = "N2_Ps", FileFilter = "Ps", cue = octanol, center_on_pulse = "ON", food = JUb39)
N2_OP <- MF.matR::plotGCaMP_multi(genotype = "N2_OP",FileFilter = "OP", cue = octanol, center_on_pulse = "ON", food = OP50)
N2 <- rbind(N2_OP$data,N2_Ps$data)
N2 %>% mutate(maxD = case_when(
maxD < 0 ~ 0,
TRUE ~ maxD)) %>%
unnest() %>% group_by(animal, animal_num, food, maxD) %>%
nest() %>% ggplot(aes(x = fct_relevel(food, "OP50"), y = maxD)) +
ggbeeswarm::geom_quasirandom(width = 0.1) +
ProvidenciaChemo::add.mean("maxD") +
ProvidenciaChemo::add.quartiles("maxD") +
#ProvidenciaChemo::add.n.categorical(group = "food") +
ProvidenciaChemo::theme_my_ppt #+
#ProvidenciaChemo::figure.axes()
#barplot
N2.maxD <- N2 %>%
mutate(maxD = case_when(
maxD < 0 ~ 0,
TRUE ~ maxD)) %>%
unnest() %>% mutate(
food = factor(food, levels = c("OP50", "JUb39"))) %>%
group_by(animal, animal_num, food, maxD) %>%
nest()
sciplot::bargraph.CI(data = N2.maxD,
x.factor = food,
response = maxD,
ylim = c(0,1.25),
col=c("#827E7E","#484CC7"),
err.width = 0.05)
N2 %>% unnest() %>% group_by(animal, animal_num, food, maxD) %>%
ggplot(aes(x = time, y = delF, color = fct_relevel(food, "OP50"))) +
geom_line(aes(group = animal), alpha = 0.2) +
geom_smooth(method = "loess", span = 0.1) +
ProvidenciaChemo::theme_my_ppt +
ProvidenciaChemo::scale_color_plot("grey-blue", drop = TRUE) +
guides(color = FALSE)
octr1 %>% unnest() %>% group_by(animal, animal_num, food, maxD) %>%
ggplot(aes(x = time, y = delF, color = fct_relevel(food, "OP50"))) +
geom_line(aes(group = animal), alpha = 0.2) +
geom_smooth(method = "loess", span = 0.1) +
ProvidenciaChemo::theme_my_ppt +
ProvidenciaChemo::scale_color_plot("grey-blue", drop = TRUE) +
guides(color = FALSE)
sciplot::bargraph.CI(data = octr1,
x.factor = food,
response = maxD,
ylim = c(0,1.5),
col=c("#827E7E","#484CC7"),
err.width = 0.05)
N2 %>% mutate(maxD = case_when(
maxD < 0 ~ 0,
TRUE ~ maxD)) %>%
unnest() %>%
group_by(animal, animal_num, food, maxD) %>%
nest() %$% wilcox.test(maxD ~ food)
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