## Load libraries
suppressPackageStartupMessages({
library(tidyverse)
library(ggplot2)
library(rlang)
library(utils)
library(data.table)
library(dumbbell)
})
## Generate Some Random Data
z<-data.frame(Group = c(rep("A",10),rep("B",10)),
Subject = c(paste("sub_",1:10,sep=""),paste("sub_",1:10,sep="")),
result = c(sample(1:100000, 20, replace=T)),
analysis = c(rep("a",5),rep("b",5) ,rep("a",5),rep("b",5) )
)
## Create 2 groups "A", "B"
b<-z %>% filter(Group == "A")
c<-z %>% filter(Group == "B")
b$Subject<-as.factor(b$Subject)
c$Subject<-as.factor(c$Subject)
d<-merge(b,c, by.x=c("Subject", "analysis"), by.y = c("Subject","analysis"))
## Order by delta
e<-d %>% mutate("diff"=pmin(result.x-result.y)) %>% arrange(diff)
d$Subject<-factor(d$Subject, e$Subject)
##Create a basic dumbell Plot
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",
lab1 = "labelA",lab2 = "labelB")
##Adding a delta column
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",
lab1 = "labelA",lab2 = "labelB",delt=1,expandx = 0.1)
##Adding values as labels
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",
lab1 = "labelA",lab2 = "labelB", pt_val = 1, expandx = 0.05, col_lab1 = "blue", col_lab2 = "red")
##Adding arrows
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",
lab1 = "labelA",lab2 = "labelB", expandx = 0.01, arrow = 1, pt_alpha = 0.6, arrow_size = 0.2,
segsize = 0.7, pointsize = 1.5, col_seg1 = "#A9A9A9", col_seg2 = "#A9A9A9")
##Adding facets
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",lab1 = "labelA",lab2 = "labelB") +
facet_wrap(analysis ~., ncol=1,scales = "free")
##Adding facets
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",lab1 = "labelA",lab2 = "labelB", pval=1) +
facet_wrap(analysis ~., ncol=1,scales = "free")
##Adding facets, highlight one direction, add arrows and the delta value
dumbbell(xdf=d,id = "Subject",key="analysis",column1 = "result.x",column2 = "result.y",lab1 = "labelA",lab2 = "labelB",
delt = 1,col_seg2 = "red", col_seg1 = "blue",arrow = 1 ,pt_alpha = 0.6, pointsize = 2 ,expandx = 0.2 ,segsize = 0.5,textsize = 2,pval=1
) +
facet_wrap(analysis ~., ncol=1,scales = "free")