Biok data wrangling
Stephen Murata
11/22/2021
1 Descriptive summary stats by variable
options(width=190)
compareGroups::descrTable(~. , Biok_vert_df, include.miss=TRUE, hide.no = '0', show.all=TRUE)##
## --------Summary descriptives table ---------
##
## _____________________________________________________________
## [ALL] N
## N=218
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## sex: 218
## male 82 (37.6%)
## female 136 (62.4%)
## age 44.3 (12.9) 218
## BMI 28.6 (5.58) 218
## race: 218
## asian 3 (1.38%)
## black 4 (1.83%)
## white 211 (96.8%)
## patientno 1016 (1365) 218
## Site_Location: 218
## Johns Hopkins 22 (10.1%)
## Univeristy of Michigan 69 (31.7%)
## Mayo Clinic 114 (52.3%)
## Pine Rest 13 (5.96%)
## infusionno: 218
## BL 73 (33.5%)
## 1st 72 (33.0%)
## 3rd 73 (33.5%)
## Blood_Draw_Event: 218
## Acute Infusion #1 Baseline 100 49 (22.5%)
## Acute Infusion #1 Baseline 40 24 (11.0%)
## Acute Infusion #1 Stop 100 48 (22.0%)
## Acute Infusion #1 Stop 40 24 (11.0%)
## Acute Infusion #3 Stop 100 28 (12.8%)
## Acute Infusion #3 Stop 40 45 (20.6%)
## Batch_Number 3.51 (1.71) 218
## BSS_Score 4.57 (6.82) 213
## MADRS_Score 17.0 (10.6) 217
## Remission: 218
## No remission 77 (35.3%)
## Remitter 138 (63.3%)
## 'Missing' 3 (1.38%)
## ResponderANDREMITTER: 218
## No response 14 (6.42%)
## Responder 63 (28.9%)
## remission 138 (63.3%)
## 'Missing' 3 (1.38%)
## TRP_nM 25449 (5942) 218
## five_HT_nM 205 (284) 218
## KYN_nM 917 (244) 218
## three_HK_nM 16.2 (7.44) 218
## KYNA_nM 19.5 (7.68) 218
## PIC_nM 19.2 (13.5) 218
## Quin_nM 146 (43.0) 218
## AA_nM 5.95 (3.12) 218
## KYN_TRP_ratio 0.04 (0.01) 218
## KYN_SER_ratio 33.2 (72.1) 218
## QUIN_PIC_ratio 9.14 (4.39) 218
## QUIN_KYNA_ratio 8.30 (3.40) 218
## threeHK_KYN_ratio 0.02 (0.01) 218
## threeHK_KYNA_ratio 0.91 (0.44) 218
## IL1B_pg_mL 0.28 (0.47) 42
## IL1B_pg_mL_LLOD 0.34 (0.19) 218
## IL2_pg_mL 1.27 (6.00) 152
## IL2_pg_mL_LLOD 0.92 (5.03) 218
## IL4_pg_mL 0.09 (0.03) 217
## IL4_pg_mL_LLOD 0.09 (0.03) 218
## IL6_pg_mL 1.04 (0.58) 218
## IL8_pg_mL 4.36 (1.66) 218
## IL10_pg_mL 0.64 (1.95) 218
## IL12p70_pg_mL 21.8 (186) 217
## IL12p70_pg_mL_LLOD 21.7 (185) 218
## IL13_pg_mL 5.07 (11.5) 215
## IL13_pg_mL_LLOD 5.01 (11.4) 218
## TNFa_pg_mL 1.44 (0.46) 218
## IFNy_pg_mL 6.97 (5.50) 218
## CRP_ng_mL 2835 (4774) 218
## NIC_nM 41.4 (340) 218
## NIC_nM_LLOD 41.4 (340) 218
## NTA_nM 306 (153) 218
## SAA_ng_mL 2870 (2145) 218
## VCAM_1_ng_mL 309 (67.9) 218
## ICAM_1_ng_mL 308 (82.3) 218
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯2 Missingness patterns
missingTable(createTable(compareGroups(infusionno ~ ., data = Biok_vert_df, method = NA), hide.no = '0', show.all = TRUE)
)##
## --------Missingness table by 'infusionno'---------
##
## ___________________________________________________________________________
## [ALL] BL 1st 3rd p.overall
## N=218 N=73 N=72 N=73
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯
## sex 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## age 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## BMI 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## race 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## patientno 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## Site_Location 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## Blood_Draw_Event 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## Sample_ID 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## Batch_Number 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## BSS_Score 5 (2.29%) 0 (0.00%) 2 (2.78%) 3 (4.11%) 0.291
## MADRS_Score 1 (0.46%) 0 (0.00%) 0 (0.00%) 1 (1.37%) 1.000
## Remission 3 (1.38%) 1 (1.37%) 1 (1.39%) 1 (1.37%) 1.000
## ResponderANDREMITTER 3 (1.38%) 1 (1.37%) 1 (1.39%) 1 (1.37%) 1.000
## TRP_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## five_HT_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## KYN_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## three_HK_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## KYNA_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## PIC_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## Quin_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## AA_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## KYN_TRP_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## KYN_SER_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## QUIN_PIC_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## QUIN_KYNA_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## threeHK_KYN_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## threeHK_KYNA_ratio 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL1B_pg_mL 176 (80.7%) 57 (78.1%) 61 (84.7%) 58 (79.5%) 0.565
## IL1B_pg_mL_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL2_pg_mL 66 (30.3%) 28 (38.4%) 20 (27.8%) 18 (24.7%) 0.168
## IL2_pg_mL_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL4_pg_mL 1 (0.46%) 0 (0.00%) 1 (1.39%) 0 (0.00%) 0.330
## IL4_pg_mL_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL6_pg_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL8_pg_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL10_pg_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL12p70_pg_mL 1 (0.46%) 0 (0.00%) 1 (1.39%) 0 (0.00%) 0.330
## IL12p70_pg_mL_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IL13_pg_mL 3 (1.38%) 1 (1.37%) 2 (2.78%) 0 (0.00%) 0.327
## IL13_pg_mL_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## TNFa_pg_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## IFNy_pg_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## CRP_ng_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## NIC_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## NIC_nM_LLOD 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## NTA_nM 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## SAA_ng_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## VCAM_1_ng_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## ICAM_1_ng_mL 0 (0.00%) 0 (0.00%) 0 (0.00%) 0 (0.00%) .
## ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯3 Outcome visual inspection (MADRS)
# Histogram analysis
ggplot(Biok_vert_df, aes(x=MADRS_Score)) +
geom_histogram( colour="black", fill="orange")+
labs(title="Histogram of MADRS total scores (N=218)")+
geom_vline(aes(xintercept=mean(MADRS_Score)),
color="blue", linetype="dashed", size=1)+
theme_gray()
mu <- ddply(Biok_vert_df, "infusionno", summarise, grp.mean=mean(MADRS_Score))
ggplot(Biok_vert_df, aes(x=MADRS_Score))+
geom_histogram(color="black", fill="orange")+
facet_grid(infusionno ~ .)+
theme(legend.position="none")+
geom_vline(data=mu, aes(xintercept=grp.mean, color=infusionno),linetype="dashed")+
labs(title="Distribution of MADRS total score by Ketamine infusion (timepoint)", x="Depressive severity (MADRS)", y="Count")+
theme_gray()
#Boxplot analysis
mylabs <- levels(Biok_vert_df$infusionno)
library(tidyverse)
Biok_vert_df %>%
ggplot(aes(x = as.numeric(infusionno), y = MADRS_Score)) +
geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 ) +
ggtitle("Depression by Ketamine Infusion (timeseries)")+
geom_line(aes(group=patientno, color=Remission)) +
geom_point(aes(color=Remission))+
labs(x = "infusionno") +
scale_x_continuous(breaks = 1:3, labels = mylabs)
4 Histograms by biomarker (whole cohort)
lab<-"Histogram: KP metabolite plasma levels (whole cohort)"
lapply(all_of(vars_KP), function(i) sfsmisc::histBxp(Biok_vert_df[ , i],
main = lab ,
xlab = i,
col = "gray",
boxcol = "green",
medcol = "red"))
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## NULLlab<-"Histogram: Inflammatory biomarker plasma levels (whole cohort)"
lapply(all_of(vars_inflam), function(i) sfsmisc::histBxp(Biok_vert_df[ , i],
main = lab ,
xlab = i,
col = "gray",
boxcol = "green",
medcol = "red"))
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## NULLlab<-"Histogram: Vascular-Endothelial biomarker plasma levels (whole cohort)"
lapply(all_of(vars_vasc), function(i) sfsmisc::histBxp(Biok_vert_df[ , i],
main = lab ,
xlab = i,
col = "gray",
boxcol = "green",
medcol = "red"))
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## NULL#
# for (scale in c(vars_KP)) {
# boxplot(Biok_vert_df[, scale] ~ infusionno, data=Biok_vert_df, ylab=scale )
# }
#
#
# for (scale in c(vars_vasc)) {
# boxplot(Biok_vert_df[, scale] ~ infusionno, data=Biok_vert_df, ylab=scale )
# }
#
#
# for (scale in c(vars_inflam)) {
# boxplot(Biok_vert_df[, scale] ~ infusionno, data=Biok_vert_df, ylab=scale )
# }Biomarkers with potential outliers: NIC_nM, NIC_nM_LLOD, IL1B_pg_mL, IL1B_pg_mL_LLOD, IL2_pg_mL_LLOD, IL12p70_pg_mL, IL12p70_pg_mL_LLOD, IL13_pg_mL, IL13_pg_mL_LLOD
5 KP biomarker boxplots by ketamine infusion no.
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = TRP_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = five_HT_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = KYN_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = three_HK_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = KYNA_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = PIC_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = Quin_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = AA_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = KYN_TRP_ratio))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = KYN_SER_ratio))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = QUIN_PIC_ratio))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = QUIN_KYNA_ratio))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = threeHK_KYN_ratio))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 ) +
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
Potentially problematic observatations: 12, 136
6 Inflammatory biomarker boxplots by ketamine infusion no.
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL1B_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL1B_pg_mL_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL2_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL2_pg_mL_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL4_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL4_pg_mL_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL6_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL8_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL10_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL10_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL12p70_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL12p70_pg_mL_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL13_pg_mL))
gg.base +geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IL13_pg_mL_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = TNFa_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = IFNy_pg_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = CRP_ng_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
Potentially problematic observations: 16, 106, 3013, 3018, 3008
7 Vascular endothelial biomarker boxplots by ketamine infusion no.
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = NIC_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = NIC_nM_LLOD))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = NTA_nM))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = SAA_ng_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = VCAM_1_ng_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
gg.base <- ggplot(Biok_vert_df, aes(x = infusionno, y = ICAM_1_ng_mL))
gg.base + geom_boxplot(aes(group = infusionno), lwd=1.25, fatten=1, outlier.shape = "triangle", outlier.size = 3 )+
geom_line(aes(color = Remission, group = patientno))+ geom_point(aes(color=Remission))+
ggrepel::geom_label_repel(aes(label = patientno),
box.padding = 0.35,
point.padding = 0.5,
segment.color = 'grey50') + ggtitle("Biomarker by Ketamine Infusion (Timeseries)")+ labs(x = "Ketamine Infusion Number") + theme_classic() 
Potentially problematic observations: 96