BM_project_exp_2_BM_imprinting

Libraries

library(tidyverse)
library(plotly)
library(ggbeeswarm)
library(ggplot2)
library(car)
library(rstatix)
library(SimComp)
library(readxl)
library(dplyr)

Dataset

dataset_exp_2_bm_imprint <- read_excel (path = "/mnt/c/Users/Toshiya Matsushima/OneDrive/R projects/BM_project/data analysis using Rstudio/BM_project_dataset.xlsx", sheet = "exp_2_3_bm_imprint")
dataset_exp_2_bm_imprint_ctrl <- filter(dataset_exp_2_bm_imprint, drug == "00_ctrl")
dataset_exp_2_bm_imprint_ctrl_vpa_keta_tubo <- filter(dataset_exp_2_bm_imprint, label == "00_ctrl_1" | label == "01_vpa_2" | label == "02_keta_2" | label == "04_tubo_2")
#dataset_exp_2_bm_imprint_ctrl_vpa_vpabume <- filter(dataset_exp_2_bm_imprint, label == "00_ctrl_1" | label == "01_vpa_2" | label == "01_vpa_2_bume")
#dataset_exp_2_bm_imprint_ctrl_bumeta_vu_vpa_vpabume <- filter(dataset_exp_2_bm_imprint, label == "00_ctrl_1" | label == "01_vpa_2" | label == "08_bume_1_e14" | label == "09_vu_1_e14" | label == "01_vpa_2_bume")
dataset_exp_2_bm_imprint_fig <- filter(dataset_exp_2_bm_imprint, fig_data == 1)
dataset_exp_2_bm_imprint_fig_2 <- filter(dataset_exp_2_bm_imprint, fig_data == 1 | fig_data == 2)

dataset_exp_2_bm_imprint

dataset_exp_2_bm_imprint_ctrl

dataset_exp_2_bm_imprint_ctrl_vpa_keta_tubo

#dataset_exp_2_bm_imprint_ctrl_vpa_vpabume
#dataset_exp_2_bm_imprint_ctrl_bumeta_vu_vpa_vpabume
dataset_exp_2_bm_imprint_fig

dataset_exp_2_bm_imprint_fig_2

Statistics of run

  dataset_exp_2_bm_imprint %>% 
  group_by (label) %>% 
  get_summary_stats(run)

Statistics of BM

  dataset_exp_2_bm_imprint %>% 
  group_by (label) %>% 
  get_summary_stats(bm)

Statistics of imprint

  dataset_exp_2_bm_imprint %>% 
  group_by (label) %>% 
  get_summary_stats(imprint)

Analysis of the control data

Correlation (Spearman) between BM and imprint scores in the control dataset

cor_test(dataset_exp_2_bm_imprint_ctrl, bm, imprint, method = "spearman")

x-y plot in the control dataset

fig <- ggplot(data = dataset_exp_2_bm_imprint_ctrl, mapping = aes(x=bm, y=imprint))+
  geom_point(size=3)+
  geom_vline(xintercept=0, linetype = "dotted")+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_smooth(method = "lm")+
  xlim(-400, 600)+
  ylim(-600, 600)+
  theme_classic()
fig

`geom_smooth()` using formula 'y ~ x'

ggsave(plot = fig, filename = "exp_2_imprint_vs_bm_control.png", dpi = 300, height = 10, width = 13, units = "cm")

`geom_smooth()` using formula 'y ~ x'

x-y plot in all data

fig <- ggplot(data = dataset_exp_2_bm_imprint_ctrl_vpa_keta_tubo, mapping = aes(x=bm, y=imprint, color=drug))+
  geom_point(size=3)+
  geom_vline(xintercept=0, linetype = "dotted")+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_smooth(method = "lm")+
  xlim(-400, 600)+
  ylim(-600, 600)+
  theme_classic()
fig

`geom_smooth()` using formula 'y ~ x'
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

ggsave(plot = fig, filename = "exp_2_imprint_vs_bm_control_vpa_keta_tubo.png", dpi = 300, height = 10, width = 13, units = "cm")

`geom_smooth()` using formula 'y ~ x'
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

fig <- ggplot(data = dataset_exp_2_bm_imprint, mapping = aes(x=bm, y=imprint, color=label))+
  geom_point(size=1)+
  facet_wrap(~drug)+
  geom_vline(xintercept=0, linetype = "dotted")+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_smooth(method = "lm")+
  xlim(-400, 600)+
  ylim(-400, 600)+
  theme_classic()
fig

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 5 rows containing non-finite values (stat_smooth).
Warning: Removed 5 rows containing missing values (geom_point).
Warning: Removed 29 rows containing missing values (geom_smooth).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

ggsave(plot = fig, filename = "exp_2_imprint_vs_bm_all_wrap.png", dpi = 300, height = 15, width = 20, units = "cm")

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 5 rows containing non-finite values (stat_smooth).
Warning: Removed 5 rows containing missing values (geom_point).
Warning: Removed 29 rows containing missing values (geom_smooth).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

fig <- ggplot(data = dataset_exp_2_bm_imprint_fig, mapping = aes(x=bm, y=imprint, color=label))+
  geom_point(size=1)+
  facet_wrap(~drug)+
  geom_vline(xintercept=0, linetype = "dotted")+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_smooth(method = "lm")+
  xlim(-400, 600)+
  ylim(-400, 600)+
  theme_classic()
fig

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 2 rows containing non-finite values (stat_smooth).
Warning: Removed 2 rows containing missing values (geom_point).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

ggsave(plot = fig, filename = "exp_2_imprint_vs_bm_fig_wrap.png", dpi = 300, height = 15, width = 20, units = "cm")

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 2 rows containing non-finite values (stat_smooth).
Warning: Removed 2 rows containing missing values (geom_point).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

Analysis of run

run all data

fig <- ggplot(data = dataset_exp_2_bm_imprint, mapping = aes(x=label, y=run))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_boxplot()+
  ylim(0, 3000)+
  geom_quasirandom(shape=16, size=2, colour="black")+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 19 rows containing non-finite values (stat_boxplot).
Warning: Removed 19 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_run_label_all.png", dpi = 300, height = 10, width = 18, units = "cm")

Warning: Removed 19 rows containing non-finite values (stat_boxplot).
Warning: Removed 19 rows containing missing values (position_quasirandom).

x-y plot in all data

fig <- ggplot(data = dataset_exp_2_bm_imprint_ctrl_vpa_keta_tubo, mapping = aes(x=run, y=imprint, color=drug))+
  geom_point(size=3)+
  geom_vline(xintercept=0, linetype = "dotted")+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_smooth(method = "lm")+
  xlim(0, 3000)+
  ylim(-600, 600)+
  theme_classic()
fig

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 12 rows containing non-finite values (stat_smooth).
Warning: Removed 12 rows containing missing values (geom_point).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

ggsave(plot = fig, filename = "exp_2_imprint_vs_run_control_vpa_keta_tubo.png", dpi = 300, height = 10, width = 13, units = "cm")

`geom_smooth()` using formula 'y ~ x'
Warning: Removed 12 rows containing non-finite values (stat_smooth).
Warning: Removed 12 rows containing missing values (geom_point).
Warning in max(ids, na.rm = TRUE) :
  no non-missing arguments to max; returning -Inf

BM linear fitting

fit_exp2_run_all <- lm (run ~ label, data = dataset_exp_2_bm_imprint)
summary (fit_exp2_run_all)

Call:
lm(formula = run ~ label, data = dataset_exp_2_bm_imprint)

Residuals:
    Min      1Q  Median      3Q     Max 
-1610.4  -689.8  -163.9   427.3  3624.9 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)          1154.11      87.50  13.190   <2e-16 ***
label01_vpa_1        -130.81     319.10  -0.410   0.6821    
label01_vpa_2         484.29     319.10   1.518   0.1300    
label01_vpa_2_bume   -591.11     319.10  -1.852   0.0648 .  
label02_keta_1       -487.81     319.10  -1.529   0.1273    
label02_keta_2       -651.81     319.10  -2.043   0.0418 *  
label02_keta_2_bume  -187.83     305.39  -0.615   0.5389    
label03_mk801_1       193.99     319.10   0.608   0.5436    
label03_mk801_2      -341.41     319.10  -1.070   0.2854    
label04_tubo_1       -396.11     319.10  -1.241   0.2153    
label04_tubo_2       -339.41     319.10  -1.064   0.2882    
label04_tubo_2_bume    47.69     319.10   0.149   0.8813    
label04_tubo_2_e10    215.89     319.10   0.677   0.4991    
label04_tubo_2_e18     48.29     319.10   0.151   0.8798    
label05_mla_1        -447.31     319.10  -1.402   0.1619    
label05_mla_2        -225.61     319.10  -0.707   0.4800    
label06_dhbe_1         18.49     319.10   0.058   0.9538    
label06_dhbe_2       -319.01     319.10  -1.000   0.3182    
label07_imi_1        -235.52     251.10  -0.938   0.3489    
label07_imi_2          63.89     239.20   0.267   0.7895    
label07_imi_3          35.59     319.10   0.112   0.9112    
label07_imi_4        -359.61     319.10  -1.127   0.2605    
label08_bume_1_e14    -65.81     319.10  -0.206   0.8367    
label09_vu_1_e14      381.89     319.10   1.197   0.2322    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 970.4 on 346 degrees of freedom
Multiple R-squared:  0.06327,   Adjusted R-squared:  0.001005 
F-statistic: 1.016 on 23 and 346 DF,  p-value: 0.4437

car::Anova(fit_exp2_run_all)

Anova Table (Type II tests)

Response: run
             Sum Sq  Df F value Pr(>F)
label      22008393  23  1.0161 0.4437
Residuals 325823984 346               

Analysis of BM

BM all data

fig <- ggplot(data = dataset_exp_2_bm_imprint, mapping = aes(x=label, y=bm))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_boxplot()+
  ylim(-400, 600)+
  geom_quasirandom(shape=16, size=2, colour="black")+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_bm_label_all.png", dpi = 300, height = 10, width = 18, units = "cm")

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

BM linear fitting

fit_exp2_bm_all <- lm (bm ~ label, data = dataset_exp_2_bm_imprint)
summary (fit_exp2_bm_all)

Call:
lm(formula = bm ~ label, data = dataset_exp_2_bm_imprint)

Residuals:
    Min      1Q  Median      3Q     Max 
-508.20 -126.80   -1.45  119.90  402.69 

Coefficients:
                      Estimate Std. Error t value Pr(>|t|)    
(Intercept)          1.363e+02  1.587e+01   8.592 2.99e-16 ***
label01_vpa_1       -5.871e+01  5.786e+01  -1.015  0.31097    
label01_vpa_2        2.609e+01  5.786e+01   0.451  0.65232    
label01_vpa_2_bume  -5.371e+01  5.786e+01  -0.928  0.35392    
label02_keta_1      -7.211e+01  5.786e+01  -1.246  0.21351    
label02_keta_2      -1.468e+02  5.786e+01  -2.537  0.01161 *  
label02_keta_2_bume -9.285e+01  5.537e+01  -1.677  0.09447 .  
label03_mk801_1     -8.943e-03  5.786e+01   0.000  0.99988    
label03_mk801_2     -9.509e+00  5.786e+01  -0.164  0.86956    
label04_tubo_1       3.539e+01  5.786e+01   0.612  0.54116    
label04_tubo_2      -1.625e+02  5.786e+01  -2.809  0.00526 ** 
label04_tubo_2_bume -7.111e+01  5.786e+01  -1.229  0.21991    
label04_tubo_2_e10  -2.821e+01  5.786e+01  -0.488  0.62619    
label04_tubo_2_e18  -4.621e+01  5.786e+01  -0.799  0.42505    
label05_mla_1       -3.891e+01  5.786e+01  -0.672  0.50173    
label05_mla_2       -1.535e+02  5.786e+01  -2.653  0.00834 ** 
label06_dhbe_1      -1.456e+02  5.786e+01  -2.517  0.01230 *  
label06_dhbe_2      -5.031e+01  5.786e+01  -0.869  0.38518    
label07_imi_1       -4.690e+01  4.553e+01  -1.030  0.30371    
label07_imi_2       -1.286e+02  4.337e+01  -2.966  0.00323 ** 
label07_imi_3       -1.328e+02  5.786e+01  -2.295  0.02231 *  
label07_imi_4       -1.557e+02  5.786e+01  -2.691  0.00747 ** 
label08_bume_1_e14  -1.222e+02  5.786e+01  -2.112  0.03539 *  
label09_vu_1_e14    -1.289e+02  5.786e+01  -2.228  0.02653 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 176 on 346 degrees of freedom
Multiple R-squared:  0.1116,    Adjusted R-squared:  0.05251 
F-statistic: 1.889 on 23 and 346 DF,  p-value: 0.008715

car::Anova(fit_exp2_bm_all)

Anova Table (Type II tests)

Response: bm
            Sum Sq  Df F value   Pr(>F)   
label      1345194  23  1.8891 0.008715 **
Residuals 10712336 346                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

BM selected data for Fig.3 (not including bumetanide treatment)

fig <- ggplot(data = dataset_exp_2_bm_imprint_fig, mapping = aes(x=label, y=bm))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_boxplot()+
  geom_quasirandom(shape=16, size=3, colour="black")+
  ylim(-400, 600)+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig
ggsave(plot = fig, filename = "exp_2_bm_label_selected.png", dpi = 300, height = 10, width = 10, units = "cm")

BM selected data for Fig.3 (including post-hatch bumetanide treatment)

fig <- ggplot(data = dataset_exp_2_bm_imprint_fig_2, mapping = aes(x=label, y=bm))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_hline(yintercept = 0, linetype="dotted")+
    geom_hline(yintercept=136.3089, linetype = "solid", color ="blue", size = 1)+     #average of the control data
    geom_hline(yintercept=38.65567, linetype = "solid", color ="darkred", size = 1)+  #5% level below the control average
    geom_hline(yintercept=-5.85836, linetype = "solid", color ="red", size = 1)+      #1% level below the control average
  geom_boxplot()+
  geom_quasirandom(shape=16, size=3, colour="black")+
  ylim(-400, 600)+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_bm_label_selected_bumetanide.png", dpi = 300, height = 10, width = 10, units = "cm")

Warning: Removed 1 rows containing non-finite values (stat_boxplot).
Warning: Removed 1 rows containing missing values (position_quasirandom).

BM linear fitting of selected data for Fig.3 (selected)

fit_exp2_bm_selected_bumetanide <- lm (bm ~ label, data = dataset_exp_2_bm_imprint_fig_2)
summary (fit_exp2_bm_selected_bumetanide)

Call:
lm(formula = bm ~ label, data = dataset_exp_2_bm_imprint_fig_2)

Residuals:
    Min      1Q  Median      3Q     Max 
-508.20 -131.83    2.12  124.44  402.69 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)          136.309     16.199   8.415 6.86e-15 ***
label01_vpa_2         26.091     59.075   0.442  0.65920    
label01_vpa_2_bume   -53.709     59.075  -0.909  0.36434    
label02_keta_2      -146.809     59.075  -2.485  0.01375 *  
label02_keta_2_bume  -92.854     56.537  -1.642  0.10206    
label03_mk801_2       -9.509     59.075  -0.161  0.87228    
label04_tubo_2      -162.509     59.075  -2.751  0.00648 ** 
label04_tubo_2_bume  -71.109     59.075  -1.204  0.23010    
label05_mla_2       -153.509     59.075  -2.599  0.01005 *  
label06_dhbe_2       -50.309     59.075  -0.852  0.39543    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 179.7 on 204 degrees of freedom
Multiple R-squared:  0.09335,   Adjusted R-squared:  0.05335 
F-statistic: 2.334 on 9 and 204 DF,  p-value: 0.01597

car::Anova(fit_exp2_bm_selected_bumetanide)

Anova Table (Type II tests)

Response: bm
           Sum Sq  Df F value  Pr(>F)  
label      677933   9  2.3339 0.01597 *
Residuals 6584059 204                  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Analysis of imprint

imprinting of all data

fig <- ggplot(data = dataset_exp_2_bm_imprint, mapping = aes(x=label, y=imprint))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_boxplot()+
  geom_quasirandom(shape=16, size=2, colour="black")+
  ylim(-400, 600)+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 3 rows containing non-finite values (stat_boxplot).
Warning: Removed 3 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_imprint_label_all.png", dpi = 300, height = 10, width = 18, units = "cm")

Warning: Removed 3 rows containing non-finite values (stat_boxplot).
Warning: Removed 3 rows containing missing values (position_quasirandom).

imprinting of all data, linear fitting

fit_exp2_imprint_all <- lm (imprint ~ label, data = dataset_exp_2_bm_imprint)
summary (fit_exp2_imprint_all)

Call:
lm(formula = imprint ~ label, data = dataset_exp_2_bm_imprint)

Residuals:
    Min      1Q  Median      3Q     Max 
-947.52 -101.49   66.64  149.48  492.70 

Coefficients:
                    Estimate Std. Error t value Pr(>|t|)    
(Intercept)           419.52      19.68  21.322  < 2e-16 ***
label01_vpa_1        -138.32      71.75  -1.928   0.0547 .  
label01_vpa_2        -316.22      71.75  -4.407  1.4e-05 ***
label01_vpa_2_bume     84.68      71.75   1.180   0.2388    
label02_keta_1        -51.82      71.75  -0.722   0.4707    
label02_keta_2       -118.62      71.75  -1.653   0.0992 .  
label02_keta_2_bume   -26.07      68.67  -0.380   0.7045    
label03_mk801_1        20.88      71.75   0.291   0.7712    
label03_mk801_2         3.88      71.75   0.054   0.9569    
label04_tubo_1         -5.82      71.75  -0.081   0.9354    
label04_tubo_2         47.08      71.75   0.656   0.5122    
label04_tubo_2_bume    -5.42      71.75  -0.076   0.9398    
label04_tubo_2_e10     78.18      71.75   1.090   0.2767    
label04_tubo_2_e18     27.38      71.75   0.382   0.7030    
label05_mla_1          61.48      71.75   0.857   0.3921    
label05_mla_2        -160.32      71.75  -2.234   0.0261 *  
label06_dhbe_1        -47.42      71.75  -0.661   0.5091    
label06_dhbe_2       -151.02      71.75  -2.105   0.0360 *  
label07_imi_1          18.24      56.46   0.323   0.7468    
label07_imi_2        -101.52      53.79  -1.887   0.0599 .  
label07_imi_3         -62.62      71.75  -0.873   0.3834    
label07_imi_4        -103.62      71.75  -1.444   0.1496    
label08_bume_1_e14    -29.72      71.75  -0.414   0.6790    
label09_vu_1_e14       -7.02      71.75  -0.098   0.9221    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 218.2 on 346 degrees of freedom
Multiple R-squared:  0.1145,    Adjusted R-squared:  0.05563 
F-statistic: 1.945 on 23 and 346 DF,  p-value: 0.006327

car::Anova(fit_exp2_imprint_all)

Anova Table (Type II tests)

Response: imprint
            Sum Sq  Df F value   Pr(>F)   
label      2130197  23  1.9452 0.006327 **
Residuals 16474517 346                    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

imprinting of selected data for Fig.3 (not including bumetanide treatment)

fig <- ggplot(data = dataset_exp_2_bm_imprint_fig, mapping = aes(x=label, y=imprint))+
  geom_hline(yintercept=0, linetype = "dotted")+
  geom_boxplot()+
  geom_quasirandom(shape=16, size=3, colour="black")+
  ylim(-400, 600)+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_imprint_label_selected.png", dpi = 300, height = 10, width = 10, units = "cm")

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

imprinting of selected data for Fig.3 (including bumetanide treatment)

fig <- ggplot(data = dataset_exp_2_bm_imprint_fig_2, mapping = aes(x=label, y=imprint))+
  geom_hline(yintercept=0, linetype = "dotted")+
    geom_hline(yintercept=419.5203, linetype = "solid", color ="blue", size = 1)+     #average of the control data
    geom_hline(yintercept=284.19273, linetype = "solid", color ="darkred", size = 1)+  #5% level below the control average
    geom_hline(yintercept=217.9088, linetype = "solid", color ="red", size = 1)+      #1% level below the control average
  geom_boxplot()+
  geom_quasirandom(shape=16, size=3, colour="black")+
  ylim(-400, 600)+
  theme_classic()+
  theme(axis.text.x = element_text(angle = 45, hjust = 1))
fig

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

ggsave(plot = fig, filename = "exp_2_imprint_label_selected_bumetanide.png", dpi = 300, height = 10, width = 10, units = "cm")

Warning: Removed 2 rows containing non-finite values (stat_boxplot).
Warning: Removed 2 rows containing missing values (position_quasirandom).

imprinting of selected data for Figure, linear fitting

fit_exp2_imprint_selected <- lm (imprint ~ label, data = dataset_exp_2_bm_imprint_fig)
summary (fit_exp2_imprint_selected)

Call:
lm(formula = imprint ~ label, data = dataset_exp_2_bm_imprint_fig)

Residuals:
   Min     1Q Median     3Q    Max 
-947.5 -100.6   78.4  152.0  492.7 

Coefficients:
                Estimate Std. Error t value Pr(>|t|)    
(Intercept)       419.52      20.66  20.311  < 2e-16 ***
label01_vpa_2    -316.22      75.33  -4.198 4.27e-05 ***
label02_keta_2   -118.62      75.33  -1.575   0.1171    
label03_mk801_2     3.88      75.33   0.052   0.9590    
label04_tubo_2     47.08      75.33   0.625   0.5328    
label05_mla_2    -160.32      75.33  -2.128   0.0347 *  
label06_dhbe_2   -151.02      75.33  -2.005   0.0465 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 229.1 on 176 degrees of freedom
Multiple R-squared:  0.1303,    Adjusted R-squared:  0.1007 
F-statistic: 4.396 on 6 and 176 DF,  p-value: 0.0003639

car::Anova(fit_exp2_imprint_selected)

Anova Table (Type II tests)

Response: imprint
           Sum Sq  Df F value    Pr(>F)    
label     1383957   6  4.3957 0.0003639 ***
Residuals 9235459 176                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

imprinting of selected data for Figure, linear fitting with BM

fit_exp2_imprint_selected_BM <- lm (imprint ~ label*bm, data = dataset_exp_2_bm_imprint_fig)
summary (fit_exp2_imprint_selected_BM)

Call:
lm(formula = imprint ~ label * bm, data = dataset_exp_2_bm_imprint_fig)

Residuals:
    Min      1Q  Median      3Q     Max 
-948.09  -80.70   58.74  143.68  333.93 

Coefficients:
                     Estimate Std. Error t value Pr(>|t|)    
(Intercept)         394.32790   25.36851  15.544  < 2e-16 ***
label01_vpa_2      -448.38281   87.86769  -5.103 8.92e-07 ***
label02_keta_2      -95.38232   75.20438  -1.268   0.2064    
label03_mk801_2     -17.62608  101.46569  -0.174   0.8623    
label04_tubo_2       75.22628   76.02530   0.989   0.3238    
label05_mla_2      -135.18053   75.65554  -1.787   0.0758 .  
label06_dhbe_2     -156.86870   85.46211  -1.836   0.0682 .  
bm                    0.18482    0.11305   1.635   0.1039    
label01_vpa_2:bm      0.78412    0.30287   2.589   0.0105 *  
label02_keta_2:bm    -0.37095    0.41052  -0.904   0.3675    
label03_mk801_2:bm    0.18346    0.54992   0.334   0.7391    
label04_tubo_2:bm    -0.07206    0.46760  -0.154   0.8777    
label05_mla_2:bm     -0.18788    0.54853  -0.343   0.7324    
label06_dhbe_2:bm     0.17612    0.48779   0.361   0.7185    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 223.5 on 169 degrees of freedom
Multiple R-squared:  0.2051,    Adjusted R-squared:  0.1439 
F-statistic: 3.354 on 13 and 169 DF,  p-value: 0.0001373

car::Anova(fit_exp2_imprint_selected_BM)

Anova Table (Type II tests)

Response: imprint
           Sum Sq  Df F value    Pr(>F)    
label     1348258   6  4.4987 0.0002962 ***
bm         368670   1  7.3808 0.0072785 ** 
label:bm   425295   6  1.4191 0.2099434    
Residuals 8441494 169                      
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

SessionInfo

sessionInfo()

R version 3.6.3 (2020-02-29)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.3 LTS

Matrix products: default
BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
 [1] LC_CTYPE=C.UTF-8       LC_NUMERIC=C           LC_TIME=C.UTF-8        LC_COLLATE=C.UTF-8     LC_MONETARY=C.UTF-8    LC_MESSAGES=C.UTF-8    LC_PAPER=C.UTF-8       LC_NAME=C              LC_ADDRESS=C           LC_TELEPHONE=C         LC_MEASUREMENT=C.UTF-8
[12] LC_IDENTIFICATION=C   

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

other attached packages:
 [1] ggbeeswarm_0.6.0 readxl_1.3.1     SimComp_3.3      rstatix_0.7.0    car_3.0-12       carData_3.0-5    plotly_4.10.0    forcats_0.5.1    stringr_1.4.0    dplyr_1.0.7      purrr_0.3.4      readr_2.1.1      tidyr_1.1.4      tibble_3.1.6     ggplot2_3.3.5   
[16] tidyverse_1.3.1 

loaded via a namespace (and not attached):
 [1] nlme_3.1-144         fs_1.5.2             lubridate_1.8.0      httr_1.4.2           tools_3.6.3          backports_1.4.1      utf8_1.2.2           R6_2.5.1             vipor_0.4.5          DBI_1.1.1            lazyeval_0.2.2       mgcv_1.8-31         
[13] colorspace_2.0-2     withr_2.4.3          tidyselect_1.1.1     compiler_3.6.3       survPresmooth_1.1-11 mratios_1.4.2        cli_3.1.0            rvest_1.0.2          xml2_1.3.3           sandwich_3.0-1       labeling_0.4.2       scales_1.1.1        
[25] mvtnorm_1.1-3        digest_0.6.29        rmarkdown_2.11       pkgconfig_2.0.3      htmltools_0.5.2      dbplyr_2.1.1         fastmap_1.1.0        htmlwidgets_1.5.4    rlang_0.4.12         rstudioapi_0.13      jquerylib_0.1.4      generics_0.1.1      
[37] farver_2.1.0         zoo_1.8-9            jsonlite_1.7.2       magrittr_2.0.1       Matrix_1.2-18        Rcpp_1.0.7           munsell_0.5.0        fansi_0.5.0          abind_1.4-5          lifecycle_1.0.1      stringi_1.7.6        multcomp_1.4-18     
[49] yaml_2.2.1           MASS_7.3-51.5        grid_3.6.3           crayon_1.4.2         lattice_0.20-40      haven_2.4.3          splines_3.6.3        hms_1.1.1            knitr_1.37           pillar_1.6.4         codetools_0.2-16     reprex_2.0.1        
[61] glue_1.6.0           evaluate_0.14        data.table_1.14.2    modelr_0.1.8         vctrs_0.3.8          tzdb_0.2.0           cellranger_1.1.0     gtable_0.3.0         assertthat_0.2.1     xfun_0.29            broom_0.7.10         survival_3.1-8      
[73] viridisLite_0.4.0    beeswarm_0.4.0       TH.data_1.1-0        ellipsis_0.3.2