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Figure1_Efficacy.R
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Figure1_Efficacy.R
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require(data.table)
require(PieDonut)
require(ggplot2)
require(RColorBrewer)
require(wesanderson)
require(grid)
require(gridExtra)
require(moonBook)
require(webr)
source('data/grob_stuff.R')
data <- fread('data/RET_master_table.tsv', header = T)
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Fig 1a/d: Pie Chart & Overall Efficacy
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
##### Pie Chart Figure 1a #####
PieDonut(data,aes(pies=Mut_Type,donuts=Tumor_Type), labelposition=2, explode = 1, labelpositionThreshold=0.5)
##### Waterfall Patient Order ######
recist_order = unique(data[,.(`Study_ID`,`RECIST_response`)])[order(`RECIST_response`, decreasing=T)]$`Study_ID`
##### Efficacy Figure 1d #####
do.waterfall = function(br, recist_order, leg.pos='none'){
w.f = ggplot(br,aes(x=factor(`Study_ID`, recist_order),
y=`RECIST_response`)) +
geom_bar(stat='identity', width=.7, fill = 'black') +
labs(x='',y='% best Change') +
theme_classic(base_size=10) +
ylim(-115,110) +
geom_point(data=br[`Target Lesion Response`=='NTL'], aes(x=factor(`Study_ID`, recist_order),y=0),shape=5,size=2.5 ,colour='black') +
geom_point(data=br[`Target Lesion Response`=='No Assessments'], aes(x=factor(`Study_ID`, recist_order),y=0),shape=18,size=4.5 ,colour='black') +
geom_hline(yintercept = 0, color = 'black', size = .4) +
geom_hline(yintercept = -30, color = '#DB4512', size = .5, linetype='dashed') +
theme(axis.text.x = element_blank(),
axis.ticks.x=element_blank(),
axis.line.y = element_line(color="black", size=.6),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
legend.key = element_blank(),
legend.background = element_blank(),
axis.line.x=element_blank()) +
guides(colour = guide_legend(override.aes = list(shape = NA)))
w.f
}
w.f = do.waterfall(data, recist_order)
#Alteration Type#
do.alttype = function(at, recist_order, leg.pos='none'){
a.t = ggplot(at) + geom_point(aes(x=factor(Study_ID, recist_order),y=1, colour=`Alt_Bin_Det`), shape=15, size=3) +
scale_colour_manual(values=c('KD_oncogenic'='#9CB770','CRD_oncogenic'='#FCB89B',
'CRD_indel_oncogenic'='#FDD29B','KD_pathogenic'='#69A583',
'CRD_pathogenic'='#EA7E82', 'TMD VUS'='grey',
'CCDC6'='#FF4E50', 'KIF5B'='#FFCA06', 'NCOA4'='#8C4B21',
'TAF3'='#B49A85', 'RUFY3'='#B49A85', 'KIF13A'='#B49A85', 'ERC1'='#B49A85',
'EML4'='#B49A85', 'KIAA1468'='#B49A85', 'CLIP1'='#B49A85', 'Unknown'='#8A9294',
'RBPMS'='#B49A85')) +
scale_y_continuous(limits=c(1,1)) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
#axis.title.y=element_text(angle=0, hjust=.5, size=10), #####
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
plot.background=element_blank(),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
plot.margin = unit(c(0,0,0,0), 'lines'),
legend.key=element_blank(),
legend.background = element_blank())
a.t
}
a.t = do.alttype(data, recist_order)
#Tumor Type#
do.tumortype = function(tt, recist_order, leg.pos='none'){
t.t = ggplot(tt) + geom_point(aes(x=factor(Study_ID, recist_order),y=1, colour=`Tumor_Type`), shape=15, size=3) +
scale_colour_manual(values=c('Papillary Thyroid'='#9dc6d8','Medullary Thyroid'='#1d4e89',
'Poorly Differentiated Thyroid'='#00b3ca',
'Lung Adenocarcinoma'='#74a089','Lung Adenosquamous'='#f69256',
'Combined Small Cell Lung Carcinoma'='#e38690',
'High-Grade Neuroendocrine Carcinoma of the Colon and Rectum'='#513c1f',
'Non Langerhans Cell Histiocytosis'='#4e5c5f')) +
scale_y_continuous(limits=c(1,1)) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
#axis.title.y=element_text(angle=0, hjust=.5, size=10), #####
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
plot.background=element_blank(),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
plot.margin = unit(c(0,0,0,0), 'lines'),
legend.key=element_blank(),
legend.background = element_blank())
t.t
}
t.t = do.tumortype(data, recist_order)
#Overall Response#
do.overallchange = function(oc, recist_order, leg.pos='none'){
my.cols = brewer.pal(8,'Dark2')
o.c = ggplot(oc) + geom_point(aes(x=factor(Study_ID, recist_order),y=1, colour=`Overall Response`), shape=15, size=3) +
scale_colour_manual(values=c('CR'='firebrick2', 'PR'='indianred1', 'SD'='#278c44', 'PD'='#0072B2','NE'='grey'),
breaks=c('CR'='firebrick2', 'PR'='indianred1', 'SD'='#278c44', 'PD'='#0072B2','NE'='grey'),
labels=c('CR'='firebrick2', 'PR'='indianred1', 'SD'='#278c44', 'PD'='#0072B2','NE'='grey'),
name='') +
scale_y_continuous(limits=c(1,1)) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
plot.background=element_blank(),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
plot.margin = unit(c(0,0,0,0), 'lines'),
legend.key=element_blank(),
legend.background = element_blank())
o.c
}
o.c = do.overallchange(data, recist_order)
#Mutation Origin#
do.conc = function(conc, recist_order, leg.pos='none'){
c.f = ggplot(conc) + geom_point(aes(x=factor(Study_ID, recist_order),y=1,colour=Mut_Type),shape=15, size=3) +
scale_colour_manual(values=c('Germline Mutation'='black','Somatic Mutation'='grey', 'Fusion'='grey')) +
scale_y_continuous(limits=c(1,1)) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_text(angle=0, hjust=.5, size=10),
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
plot.background=element_blank(),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
plot.margin = unit(c(0,0,0,0), 'lines'),
legend.key=element_blank(),
legend.background = element_blank())
c.f
}
c.f = do.conc(data, recist_order)
## Previous RET TKI ##
do.prev = function(prev, recist_order, leg.pos='none'){
p.v = ggplot(prev) + geom_point(aes(x=factor(Study_ID, recist_order),y=1,colour=Previous_TKI),shape=15, size=3) +
scale_colour_manual(values=c('Yes'='black','No'='grey')) +
scale_y_continuous(limits=c(1,1)) +
theme(axis.line=element_blank(),
axis.text.x=element_blank(),
axis.text.y=element_blank(),
axis.ticks=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_text(angle=0, hjust=.5, size=10),
panel.background=element_blank(),
panel.border=element_blank(),
panel.grid.major=element_blank(),
panel.grid.minor=element_blank(),
plot.background=element_blank(),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
plot.margin = unit(c(0,0,0,0), 'lines'),
legend.key=element_blank(),
legend.background = element_blank())
p.v
}
p.v = do.prev(data, recist_order)
#Duration#
do.duration = function(dr, recist_order, leg.pos='none'){
my.cols = brewer.pal(9,'Blues')
o.d = ggplot(dr,aes(x=factor(Study_ID, recist_order),
y=Weeks)) +
geom_bar(stat='identity',width=.7, fill='grey') +
labs(x='',y='Duration (wks)') +
theme_classic(base_size=10) +
geom_hline(yintercept = 0, color = 'black', size = .4) +
ylim(0,130) +
theme(axis.text.x = element_blank(),
axis.ticks.x=element_blank(),
axis.line.y = element_line(color="black", size=.7),
legend.key.size=unit(0.35,'cm'),
legend.position=leg.pos,
legend.key = element_blank(),
legend.background = element_blank(),
axis.line.x=element_blank()) +
geom_point(data=dr[`Ongoing`=='YES'],aes(x=factor(Study_ID, recist_order),y=Weeks+1),shape=17,size=2.4 ,colour='grey') +
guides(colour = guide_legend(override.aes = list(shape = NA)))
o.d
}
o.d = do.duration(data, recist_order)
w.f.f = w.f + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
a.t.f = a.t + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
t.t.f = t.t + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
o.c.f = o.c + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
c.f.f = c.f + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
p.v.f = p.v + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
o.d.f = o.d + facet_grid(.~Alt_Type,scales='free_x',space='free_x') + theme(strip.background = element_blank(), strip.text = element_blank())
p.grobs = align.grobs(list(w.f.f, a.t.f, t.t.f, o.c.f, c.f.f, p.v.f, o.d.f))
c.plot <- grid.arrange(arrangeGrob(p.grobs[[1]],p.grobs[[2]],p.grobs[[3]],p.grobs[[4]],p.grobs[[5]],p.grobs[[6]],p.grobs[[7]],
heights=c(.5, .1, .1, .1, .1, .1, .2)))