/
alkati_crizotinib_ic50s.Rmd
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alkati_crizotinib_ic50s.Rmd
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---
title: "alkati_crizotinib_ic50s"
author: "Haider Inam"
date: "1/25/2021"
output: html_document
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(root.dir=rprojroot::find_rstudio_root_file())
```
```{r}
library(plotly)
library(knitr)
library(tictoc)
library(workflowr)
library(VennDiagram)
library(dplyr)
library(foreach)
library(doParallel)
library(ggplot2)
library(reshape2)
library(RColorBrewer)
library(devtools)
library(ggsignif)
library(plotly)
library(BiocManager)
library(drc)
cleanup=theme_bw() +
theme(plot.title = element_text(hjust=.5),
panel.grid.major = element_blank(),
panel.grid.major.y = element_blank(),
panel.background = element_blank(),
# axis.line = element_line(color = "black"),
axis.text = element_text(face="bold",color="black",size="11"),
text=element_text(size=11,face="bold"),
axis.title=element_text(face="bold",size="11"))
```
```{r}
# rm(list=ls())
# ic50_all=read.csv("../data/alkati_baf3_ic50s_heatmap.csv",header = T,stringsAsFactors = F)
ic50_all=read.csv("data/alkati_baf3_ic50s_heatmap.csv",header = T,stringsAsFactors = F)
ic50_all=ic50_all%>%
mutate(transgene=case_when(CellLine%in%c("ALK-ATI-2018-1",
"ALK-ATI-2018-2",
"ALK-ATI-2018-3",
"ALK-ATI-2017-1",
"ALK-ATI-2017-2",
"ALK-ATI-2017-3")~"ALKATI",
CellLine%in%c("EML4-ALK 2017",
"EML4-ALK 2018")~"EML4ALK",
CellLine%in%"BaF3 PIG"~"PIG"))
ic50_all_melt=melt(ic50_all,id.vars = c("Drug","Date","transgene","CellLine","Replicate"),measure.vars =c("X500","X250","X125","X62.5","X31.25","X15.625","X7.8125","X3.90625","X1.953125"),variable.name = "conc" ,value.name = "doseresponse")
ic50_all_melt=ic50_all_melt%>%mutate(conc=as.numeric(gsub("X","",conc)))
ic50_sum_byreplicate=ic50_all_melt%>%
group_by(Drug,Date,transgene,CellLine,conc)%>%
summarize(doseresponse_mean=mean(doseresponse),doseresponse_sd=sd(doseresponse))
plotly=
ggplot(ic50_sum_byreplicate%>%filter(Drug=="crizotinib"),aes(x=conc,y=doseresponse_mean,color=transgene,fill=CellLine,shape=Date))+
geom_point()+
geom_line()+
facet_wrap(~transgene)+
scale_y_continuous(name="Response")+
scale_x_continuous(trans = "log10",name="Dose(nM)")+
cleanup
ggplotly(plotly)
ic50_sum_bydate=ic50_sum_byreplicate%>%
group_by(Drug,transgene,CellLine,conc)%>%
summarize(doseresponse_mean_acrossdates=mean(doseresponse_mean),doseresponse_sd_bydate=sd(doseresponse_mean))
###Crizotinib###
ggplot(ic50_sum_bydate%>%filter(Drug=="crizotinib"),aes(x=conc,y=doseresponse_mean_acrossdates,color=transgene,fill=CellLine))+
geom_point()+
geom_line()+
# facet_wrap(~transgene)+
scale_y_continuous(name="Response")+
scale_x_continuous(trans = "log10",name="Dose(nM)")+
cleanup
###Brigatinib###
ggplot(ic50_sum_bydate%>%filter(Drug=="brigatinib"),aes(x=conc,y=doseresponse_mean_acrossdates,color=transgene,fill=CellLine))+
geom_point()+
geom_line()+
# facet_wrap(~transgene)+
scale_y_continuous(name="Response")+
scale_x_continuous(trans = "log10",name="Dose(nM)")+
cleanup
####Looking at variation of dose responses across ALKATI lines
ggplot(ic50_sum_bydate%>%filter(transgene=="ALKATI",Drug=="crizotinib"),aes(x=conc,y=doseresponse_mean_acrossdates,fill=CellLine))+
geom_point()+
geom_line()+
geom_ribbon(aes(ymin=doseresponse_mean_acrossdates-doseresponse_sd_bydate,ymax=doseresponse_mean_acrossdates+doseresponse_sd_bydate,alpha=.3))+
scale_y_continuous(name="Response")+
scale_x_continuous(trans = "log10",name="Dose(nM)")+
cleanup+
theme(legend.position = "none")
ic50_sum_bydate_byCellLine=ic50_sum_byreplicate%>%
group_by(Drug,transgene,conc)%>%
summarize(doseresponse_sd=sd(doseresponse_mean),
doseresponse_mean=mean(doseresponse_mean))
ggplot(ic50_sum_bydate_byCellLine%>%filter(Drug=="crizotinib"),aes(x=conc,y=doseresponse_mean,fill=transgene))+
geom_ribbon(aes(ymin=doseresponse_mean-doseresponse_sd,ymax=doseresponse_mean+doseresponse_sd,alpha=.3))+
geom_line()+
geom_point(color="black",shape=21,size=3,aes(fill=factor(transgene)))+
scale_y_continuous(name="Dose Response")+
scale_x_continuous(trans = "log10",name="Dose (nM)")+
cleanup+
scale_fill_brewer(palette="Set2")+
theme(legend.position = "none")
# ggsave("baf3_alkati_criz.pdf",width=3,height=2.5,units="in",useDingbats=F)
ggplot(ic50_sum_bydate_byCellLine%>%filter(Drug=="brigatinib"),aes(x=conc,y=doseresponse_mean,fill=transgene))+
geom_ribbon(aes(ymin=doseresponse_mean-doseresponse_sd,ymax=doseresponse_mean+doseresponse_sd,alpha=.3))+
geom_line()+
geom_point(color="black",shape=21,size=3,aes(fill=factor(transgene)))+
scale_y_continuous(name="Dose Response")+
scale_x_continuous(trans = "log10",name="Dose (nM)")+
cleanup+
scale_fill_brewer(palette="Set2")+
theme(legend.position = "none")
# ggsave("baf3_alkati_brig.pdf",width=3,height=2.5,units="in",useDingbats=F)
```