20170717_20170611_thp1_bcggfp_ltr_compound_02hrs.Rmd

---
title: "20170717_20170611_thp1_bcggfp_ltr_compound_02hrs"
author: "MANISHA"
date: "July 18, 2017"
output: 
    html_document: 
        code_folding: hide
        fig_caption: yes
        fig_height: 8
        fig_width: 12
        fontsize: 10pt
        toc_float: 
        collapsed: false    
        smooth_scroll: FALSE
---

# Load the config

In this file there is experiment that is analysed.
- IMAGING - Z - PERKIN ELMER


This experiments was performed by Manisha in PE SPINNING DISC to check the  effects of 3 compounds (test+dmso) at 1 doses - 10uM & 1 timepoint - 02 hrs on THP1 macrophages upon infection -  BCG.

```{r, eval=TRUE, message=FALSE, warning=FALSE}
library(magrittr)
library(dplyr)
library(ggplot2)
source("R/ggtheme_jack.R")
source("R/fun_multiplot.R")
ggplot2::theme_set(theme_jack())

stats_mean <- "TRUE"
filter_mean <- "TRUE"
fit_plots <- "TRUE"

base_path <- c("../../../data")

exp_name_file <- c("20170717_20170611_thp1_bcggfp_ltr_compound_02hrs_Cells")
exp_name_layout <- c("20170717_20170611_thp1_bcggfp_ltr_compound_02hrs_layout")

dat <- readr::read_csv(sprintf("%s/%s.csv",base_path, exp_name_file))


dat_layout <- readr::read_csv(sprintf("%s/%s.csv",base_path, exp_name_layout))


dat <- inner_join(dat,dat_layout, by = "Metadata_Series")


```
# name to plot the data

```{r, message=FALSE, eval=fit_plots}

unique(dat$Children_GCH_Count)

dat$Metadata_InfStatus[dat$Metadata_Infection == "INF" & dat$Children_GCH_Count == 0] <-  "Bystander" 
dat$Metadata_InfStatus[dat$Metadata_Infection == "INF" & dat$Children_GCH_Count > 0] <-  "Inf" 
dat$Metadata_InfStatus[dat$Metadata_Infection == "UNINF" & dat$Children_GCH_Count == 0] <-  "Unexp"
dat$Metadata_InfStatus[dat$Metadata_Infection == "UNINF" & dat$Children_GCH_Count > 0] <-  "Inf"

unique(dat$Metadata_InfStatus)

dat$Metadata_Status <- paste(dat$Metadata_Treatment, dat$Metadata_InfStatus, sep="_")

unique(dat$Metadata_Status)

dat$Metadata_Treatment[dat$Metadata_Treatment == "A13"] <- "C23"
dat$Metadata_Treatment[dat$Metadata_Treatment == "A21"] <- "C16"
dat$Metadata_Treatment[dat$Metadata_Treatment == "A20"] <- "C1"

```

# select the data

```{r, message=FALSE, eval=stats_mean}


dat %<>%
  select(
    contains("Metadata"),
    contains("Children"),
    contains("AreaShape_Area"),
    contains("Intensity_IntegratedIntensity"),
    contains("Object_Number")
    )

dat %<>% 
  select(
    -contains("Edge"), 
    -contains("Frame"), 
    -contains("Channel"),
    -contains("Site"),
    -contains("FileLocation"),
    -contains("ColorFormat"),
    -contains("Plate"),
    -contains("Size")
    )


```


# filter the data

```{r, message=FALSE, eval=filter_mean}


p1 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigBCH)) + geom_density() + xlim(0,12000)
p2 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigGCH)) + geom_density() + xlim(0,5000)
p3 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density() + xlim(0,8000)
p4 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density() + xlim(0,2500)

multiplot(p1,p2,p3,p4, cols = 2)

n1 <- nrow(dat)

dat %<>% 
  filter(Intensity_IntegratedIntensity_OrigBCH > 10 & Intensity_IntegratedIntensity_OrigBCH < 12000)
n2 <- nrow(dat)

n1
n2

cells_filtered <- (n1-n2)*100/n1

sprintf("Percentage of cells filtered out: %s", cells_filtered)


p1 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigBCH)) + geom_density() + xlim(0,12000)
p2 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigGCH)) + geom_density() + xlim(0,5000)
p3 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density() + xlim(0,8000)
p4 <- dat %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density() + xlim(0,2500)


multiplot(p1,p2,p3,p4, cols = 2)

```


# plot the data - FINAL PLOTS - BCG

```{r, message=FALSE, eval=fit_plots}


p1 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigRCH),
           color = Metadata_InfStatus)) + ylim(0,5000) +
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles",
    x="COMPOUND TREATMENT")



p2 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = Intensity_IntegratedIntensity_OrigRCH,
           color = Metadata_InfStatus)) + ylim(0,5000) +
  facet_grid(~ Metadata_Treatment) +
  geom_violin() +
  geom_dotplot(binaxis = "y", stackdir = "center", binwidth = 20) + 
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = (Children_RCH_Count),
           color = Metadata_InfStatus)) + ylim(0,120) +
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles",
    x="COMPOUND TREATMENT")



p4 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = Children_RCH_Count,
           color = Metadata_InfStatus)) + ylim(0,100) +
  facet_grid(~ Metadata_Treatment) +
  geom_violin() +
  geom_dotplot(binaxis = "y", stackdir = "center", binwidth = 0.2) + 
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles",
    x="COMPOUND TREATMENT")

multiplot(p1,p2,p3,p4, cols = 2)



p1 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigDRCH),
           color = Metadata_InfStatus)) + ylim(0,2200) +
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Tfn positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Tfn positive vesicles",
    x="COMPOUND TREATMENT")

p2 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = Intensity_IntegratedIntensity_OrigDRCH,
           color = Metadata_InfStatus)) + ylim(0,2200) +
  facet_grid(~ Metadata_Treatment) +
  geom_violin() +
  geom_dotplot(binaxis = "y", stackdir = "center", binwidth = 10) + 
  labs(
    title="Tfn positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Tfn positive vesicles",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = (Children_DRCH_Count),
           color = Metadata_InfStatus)) + ylim(0,150) +
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Tfn positive vesicles count at 02 hpi in BCG",
    y="Count of Tfn positive vesicles",
    x="COMPOUND TREATMENT")

p4 <- ggplot(dat,
         aes(
           x = Metadata_InfStatus,
           y = Children_DRCH_Count,
           color = Metadata_InfStatus)) + ylim(0,150) +
  facet_grid(~ Metadata_Treatment) +
  geom_violin() +
  geom_dotplot(binaxis = "y", stackdir = "center", binwidth = 0.5) + 
  labs(
    title="Tfn positive vesicles count at 02 hpi in BCG",
    y="Count of Tfn positive vesicles",
    x="COMPOUND TREATMENT")

multiplot(p1,p2,p3,p4, cols = 2)




p1 <- dat %>% filter(dat$Metadata_Treatment == "DMSO") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1) + xlim(-2000,5000) + labs(title="Tfn positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p2 <- dat %>% filter(dat$Metadata_Treatment == "C23") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1) + xlim(-2000,5000) + labs(title="Tfn positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p3 <- dat %>% filter(dat$Metadata_Treatment == "C1") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1) + xlim(-2000,5000) + labs(title="Tfn positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p4 <- dat %>% filter(dat$Metadata_Treatment == "C16") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigDRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1) + xlim(-2000,5000) + labs(title="Tfn positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

multiplot(p1,p2,p3,p4, cols = 2)


p1 <- dat %>% filter(dat$Metadata_Treatment == "DMSO") %>% ggplot(aes(Children_DRCH_Count)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1, adjust = 1.8) + xlim(-100,500) + labs(title="Tfn positive vesicles count at 02 hpi in BCG")



multiplot(p1,p2,p3,p4, cols = 2)


p1 <- dat %>% filter(dat$Metadata_Treatment == "DMSO") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1, adjust = 1.8) + xlim(-2000,10000)+ labs(title="Lysotracker positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p2 <- dat %>% filter(dat$Metadata_Treatment == "C23") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1, adjust = 1.8) + xlim(-2000,10000)+ labs(title="Lysotracker positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p3 <- dat %>% filter(dat$Metadata_Treatment == "C1") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1, adjust = 1.8) + xlim(-2000,10000)+ labs(title="Lysotracker positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

p4 <- dat %>% filter(dat$Metadata_Treatment == "C16") %>% ggplot(aes(Intensity_IntegratedIntensity_OrigRCH)) + geom_density(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=.1, adjust = 1.8) + xlim(-2000,10000)+ labs(title="Lysotracker positive vesicles intensity at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

multiplot(p1,p2,p3,p4, cols = 2)
 


 
p1 <- dat %>% filter(dat$Metadata_Treatment == "DMSO") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

 
p2 <- dat %>% filter(dat$Metadata_Treatment == "C23") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

 
p3 <- dat %>% filter(dat$Metadata_Treatment == "C1") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)

 
p4 <- dat %>% filter(dat$Metadata_Treatment == "C16") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_InfStatus), fill=factor(Metadata_InfStatus)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_Treatment)


multiplot(p1,p2,p3,p4, cols = 2)


p1 <- dat %>% filter(dat$Metadata_InfStatus == "Inf") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)

p2 <- dat %>% filter(dat$Metadata_InfStatus == "Bystander") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)

p3 <- dat %>% filter(dat$Metadata_InfStatus == "Unexp") %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=1) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)


multiplot(p1,p2,p3, cols = 2)


p1 <- dat %>% filter(dat$Metadata_InfStatus == "Inf") %>% ggplot(aes(Children_RCH_Count)) + geom_density(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=0.1) + xlim(-20,120) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)

p2 <- dat %>% filter(dat$Metadata_InfStatus == "Bystander") %>% ggplot(aes(Children_RCH_Count)) + geom_density(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=0.1) + xlim(-20,120) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)

p3 <- dat %>% filter(dat$Metadata_InfStatus == "Unexp") %>% ggplot(aes(Children_RCH_Count)) + geom_density(aes(color=factor(Metadata_Treatment), fill=factor(Metadata_Treatment)), size=1, alpha=0.1) + xlim(-20,120) + labs(title="Lysotracker positive vesicles count at 02 hpi in BCG") + facet_grid(~ Metadata_InfStatus)



multiplot(p1,p2,p3, cols = 1)

```



# plot the data - FINAL PLOTS - BCG - scatter plots

```{r, message=FALSE, eval=fit_plots}


p1 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C23" & Metadata_Treatment != "C1"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigDRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Tfn per cell intensity vs BCG per cell intensity for Compound C16 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell transferrin intensity")


p2 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C23" & Metadata_Treatment != "C16"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigDRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Tfn per cell intensity vs BCG per cell intensity for Compound C1 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell transferrin intensity")


p3 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C1" & Metadata_Treatment != "C16"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigDRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Tfn per cell intensity vs BCG per cell intensity for Compound C23 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell transferrin intensity")

multiplot(p1,p2,p3, cols = 2)


p1 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C23" & Metadata_Treatment != "C1"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Lysotracker per cell intensity vs BCG per cell intensity for Compound C16 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell lysotracker intensity")


p2 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C23" & Metadata_Treatment != "C16"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Lysotracker per cell intensity vs BCG per cell intensity for Compound C1 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell lysotracker intensity")


p3 <- ggplot(dat %>% filter(Metadata_InfStatus != "Unexp" & Metadata_Treatment != "C1" & Metadata_Treatment != "C16"),
         aes(
           x = log(Intensity_IntegratedIntensity_OrigRCH),
           y = log(Intensity_IntegratedIntensity_OrigGCH), color = Metadata_Treatment)) + 
  geom_point(aes(), size =1.5) +xlim(-10,25) +ylim(-10,25) + scale_color_manual(values = c("black", "red"))+
  labs(
    title="Lysotracker per cell intensity vs BCG per cell intensity for Compound C23 compared to DMSO",
    y="log transformed per cell bacterial intensity",
    x="log transformed per cell lysotracker intensity")

multiplot(p1,p2,p3, cols = 2)



```

# binned intensity plots on basis og GCH-BCG

```{r, message=FALSE, eval=fit_plots}


dat %>% ggplot(aes(Children_GCH_Count)) + geom_density()
dat %>% ggplot(aes(Children_GCH_Count)) + geom_freqpoly()




dat1 <- filter(dat, Children_GCH_Count > 0 & Children_GCH_Count < 5)

dat2 <- filter(dat, Children_GCH_Count > 5 & Children_GCH_Count < 25)

dat3 <- filter(dat, Children_GCH_Count > 25 & Children_GCH_Count < 50)

dat4 <- filter(dat, Children_GCH_Count > 50)




p1 <- ggplot(dat1,
         aes(
           x = Metadata_InfStatus,
           y = (Children_RCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles in bin 1",
    x="COMPOUND TREATMENT")


p2 <- ggplot(dat2,
         aes(
           x = Metadata_InfStatus,
           y = (Children_RCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles in bin 2",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat3,
         aes(
           x = Metadata_InfStatus,
           y = (Children_RCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles in bin 3",
    x="COMPOUND TREATMENT")

p4 <- ggplot(dat4,
         aes(
           x = Metadata_InfStatus,
           y = (Children_RCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles count at 02 hpi in BCG",
    y="Count of Lysotracker positive vesicles in bin 4",
    x="COMPOUND TREATMENT")

multiplot(p1,p2,p3,p4, cols=2)



#######

p1 <- ggplot(dat1,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigRCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles in bin 1",
    x="COMPOUND TREATMENT")


p2 <- ggplot(dat2,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigRCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles in bin 2",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat3 ,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigRCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles in bin 3",
    x="COMPOUND TREATMENT")


p4 <- ggplot(dat4,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigRCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) +  
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="Lysotracker positive vesicles intensity at 02 hpi in BCG",
    y="Whole Cell Int-Intensity of Lysotracker positive vesicles in bin 4",
    x="COMPOUND TREATMENT")

multiplot(p1,p2,p3,p4, cols=2)


```



# binned intensity plots on basis og RCH-lysotracker

```{r, message=FALSE, eval=fit_plots}


dat %>% ggplot(aes(Children_RCH_Count)) + geom_density()
dat %>% ggplot(aes(Children_RCH_Count)) + geom_freqpoly()




dat1 <- filter(dat, Children_RCH_Count > 0 & Children_RCH_Count < 5)

dat2 <- filter(dat, Children_RCH_Count > 5 & Children_RCH_Count < 25)

dat3 <- filter(dat, Children_RCH_Count > 25 & Children_RCH_Count < 50)

dat4 <- filter(dat, Children_RCH_Count > 50)




p1 <- ggplot(dat1 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Children_GCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG count at 02 hpi in lysotracker positive vesicles",
    y="Count of BCG in bin 1",
    x="COMPOUND TREATMENT")


p2 <- ggplot(dat2 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Children_GCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG count at 02 hpi in lysotracker positive vesicles",
    y="Count of BCG in bin 2",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat3 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Children_GCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG count at 02 hpi in lysotracker positive vesicles",
    y="Count of BCG in bin 3",
    x="COMPOUND TREATMENT")

p4 <- ggplot(dat4 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Children_GCH_Count),
           color = Metadata_InfStatus)) + 
  facet_grid(~ Metadata_Treatment) +
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG count at 02 hpi in lysotracker positive vesicles",
    y="Count of BCG in bin 4",
    x="COMPOUND TREATMENT")


multiplot(p1,p2,p3,p4, cols=2)


#######

p1 <- ggplot(dat1 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigGCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG intensity at 02 hpi in lysotracker positive vesicles",
    y="Whole Cell Int-Intensity of BCG in bin 1",
    x="COMPOUND TREATMENT")


p2 <- ggplot(dat2 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigGCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG intensity at 02 hpi in lysotracker positive vesicles",
    y="Whole Cell Int-Intensity of BCG in bin 2",
    x="COMPOUND TREATMENT")


p3 <- ggplot(dat3 %>% filter(Metadata_InfStatus == "Inf") ,
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigGCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) + 
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG intensity at 02 hpi in lysotracker positive vesicles",
    y="Whole Cell Int-Intensity of BCG in bin 3",
    x="COMPOUND TREATMENT")


p4 <- ggplot(dat4 %>% filter(Metadata_InfStatus == "Inf"),
         aes(
           x = Metadata_InfStatus,
           y = (Intensity_IntegratedIntensity_OrigGCH),
           color = Metadata_InfStatus)) +
  facet_grid(~ Metadata_Treatment) +  
  geom_boxplot(outlier.shape = NA)+
  labs(
    title="BCG intensity at 02 hpi in lysotracker positive vesicles",
    y="Whole Cell Int-Intensity of BCG in bin 4",
    x="COMPOUND TREATMENT")


multiplot(p1,p2,p3,p4, cols=2)