inst/doc/package-overview.R
In lengning/gClinBiomarker: gClinBiomarker: an R package for clinical biomarker analyses
## ----setup, include=FALSE------------------------------------------------
if (!require(gClinBiomarker)) {
install_github("lengning/gClinBiomarker")
library(gClinBiomarker)
}
library(knitr)
## ---- warning=FALSE, message=FALSE, eval=FALSE---------------------------
# library(devtools)
# install_github("lengning/gClinBiomarker")
## ----warning=FALSE, message=FALSE, eval=FALSE----------------------------
# library(gClinBiomarker)
## ------------------------------------------------------------------------
head(input)
str(input)
## ------------------------------------------------------------------------
SummaryVars(data=input, trt='Arm', subgroup='BEP', var=c('Sex','Age'),
var.class=c('categorical','numeric'))
## ------------------------------------------------------------------------
kable(
SummaryVars(data=input, trt='Arm', subgroup='BEP', var=c('Sex','Age'),
var.class=c('categorical','numeric'))
)
## ---- fig.height=5, fig.width=10-----------------------------------------
CompareKM(data=input,tte='PFS', cen='PFS.event',trt='Arm', bep='BEP')
## ---- fig.height=7,fig.width=10------------------------------------------
PlotTabForestMulti(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var=c("Sex","Weight"),
bep="BEP",bep.indicator=1, compare.bep.itt=TRUE
)
## ------------------------------------------------------------------------
input.bep <- subset(input, BEP==1) # dataset with only BEP samples
kable(
CoxTab(data=input,tte="PFS", cens="PFS.event", var='Arm',
var.class="categorical"),
caption="full population, unadjusted"
)
kable(
CoxTab(data=input,tte="PFS", cens="PFS.event", var=c('Arm','Sex',"Weight"),
var.class=c("categorical","categorical","numeric")),
caption="full population, adjusted for Sex, Weight"
)
kable(
CoxTab(data=input.bep,tte="PFS", cens="PFS.event", var='Arm',
var.class="categorical"),
caption="BEP, unadjusted"
)
kable(
CoxTab(data=input.bep,tte="PFS", cens="PFS.event", var=c('Arm','Sex',"Weight"),
var.class=c("categorical","categorical","numeric")),
caption="BEP, adjusted for Sex, Weight"
)
## ----fig.width=12, fig.height=8------------------------------------------
PlotProperty(data=input, biomarker.var="KRAS.exprs", biomarker.class="numeric",
var=c("Sex", "Country"), var.class=c("categorical", "categorical"),
log2=TRUE, par.param = list(mfrow=c(2,3)))
## ----fig.width=8, fig.height=4-------------------------------------------
input.ctrl <- subset(input, Arm=="CTRL") ## Data with only ctrl samples
res.multicut.ctrl <- PlotTabForestBiomarker(data=input.ctrl,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="CTRL",
greater=TRUE, less=FALSE)
input.trt <- subset(input, Arm=="TRT") ## Data with only trt samples
res.multicut.trt <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="TRT",
greater=TRUE, less=FALSE)
## ---- fig.height=5,fig.width=10------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=5,fig.width=10------------------------------------------
res.withinbin <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
within.bin=TRUE,
show.itt=TRUE, show.bep=TRUE)
## ------------------------------------------------------------------------
stepp.out <- PlotSTEPP(data = input,
outcome.var = c("PFS", "PFS.event"),
outcome.class = "survival",
trt = "Arm",
var = "KRAS.exprs",
placebo.code = "CTRL",
active.code = "TRT"
)
## ---- fig.height=5,fig.width=8-------------------------------------------
res.subgroups.cut <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=NULL,
numerical.cutoff=100, within.bin=TRUE,
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=5,fig.width=10------------------------------------------
input$KRAS.exprs.2group <- ifelse(input$KRAS.exprs >= 100, ">=100","<100")
input$KRAS.exprs.2group <- factor(input$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
res.subgroups.bi <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs.2group",
var.class="categorical",
show.itt=TRUE, show.bep=TRUE)
## ----include=TRUE,fig.width=9, fig.height=9------------------------------
PlotKM(data=input, tte="PFS",cen="PFS.event", bep="BEP",
main="PFS BEP by treatment, by KRAS expression subgroups",
var=c("Arm","KRAS.exprs.2group"), legend.loc="topright",
plot.median=TRUE)
## ------------------------------------------------------------------------
input.bep <- subset(input, BEP==1)
kable(
SummaryVars(data=input.bep,trt='Arm', subgroup='KRAS.exprs.2group', var=c('Sex'),
var.class="categorical", subgroup.indicator=">=100",compare.subgroup=TRUE, subgroup.name="exprs")
)
## ---- fig.height=7,fig.width=10------------------------------------------
res.subgroup.cov <- PlotTabForestMulti(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var=c("Sex","Weight"),
compare.bep.itt=FALSE,
compare.subgroup=TRUE,
subgroup="KRAS.exprs.2group"
)
## ------------------------------------------------------------------------
input.trt <- subset(input, Arm=="TRT")
## ------------------------------------------------------------------------
kable(
SummaryVars(data=input.trt, trt=NULL, subgroup='BEP', var=c('Age','Sex'),
var.class=c('numeric','categorical'))
)
## ---- fig.height=5, fig.width=5------------------------------------------
CompareKM(data=input.trt,tte='PFS', cen='PFS.event',trt=NULL, bep='BEP')
## ---- fig.height=7,fig.width=10------------------------------------------
PlotTabForestMulti(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var=c("Sex","Weight"),
bep="BEP",bep.indicator=1, compare.bep.itt=TRUE
)
## ------------------------------------------------------------------------
input.trt.bep <- subset(input.trt, BEP==1) # dataset with only BEP samples
kable(
CoxTab(data=input.trt,tte="PFS", cens="PFS.event", var=c('Sex',"Weight"),
var.class=c("categorical","numeric")),
caption="the full population, model of Sex, Weight"
)
kable(
CoxTab(data=input.trt.bep,tte="PFS", cens="PFS.event", var=c('Sex',"Weight"),
var.class=c("categorical","numeric")),
caption="BEP, model of Sex, Weight"
)
## ----fig.width=7, fig.height=4-------------------------------------------
PlotProperty(data=input.trt, biomarker.var="KRAS.exprs", biomarker.class="numeric",
var=c("Sex", "Country"), var.class=c("categorical", "categorical"),
log2=TRUE, par.param = list(mfrow=c(1,2)))
## ---- fig.height=5,fig.width=8-------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=FALSE, show.bep=FALSE)
## ---- fig.height=4,fig.width=8-------------------------------------------
res.subgroups.cut <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=NULL,
numerical.cutoff=100,
greater=TRUE,less=FALSE,
show.itt=FALSE, show.bep=FALSE)
## ---- fig.height=4,fig.width=9-------------------------------------------
input.trt$KRAS.exprs.trt.2group <- ifelse(input.trt$KRAS.exprs >= 100, ">=100","<100")
input.trt$KRAS.exprs.2group <- factor(input.trt$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
res.subgroups.bi <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs.trt.2group",
var.class="categorical",
show.itt=FALSE, show.bep=FALSE)
## ----include=TRUE,fig.width=7, fig.height=7------------------------------
PlotKM(data=input.trt, tte="PFS",cen="PFS.event", bep="BEP",
main="PFS in BEP, by KRAS expression subgroups, single arm",
var=c("KRAS.exprs.trt.2group"), legend.loc="topright",
plot.median=TRUE)
## ------------------------------------------------------------------------
input.trt.bep <- subset(input.trt, BEP==1)
kable(
SummaryVars(data=input.trt.bep,trt=NULL, subgroup='KRAS.exprs.2group', var=c('Sex'),
var.class="categorical", subgroup.indicator=">=100",compare.subgroup=TRUE, subgroup.name="exprs")
)
## ---- fig.height=4,fig.width=9-------------------------------------------
res.subgroups.cat <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.mutant",
var.class="categorical",
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=4,fig.width=9-------------------------------------------
res.subgroups.cat <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.mutant",
var.class="categorical")
## ---- fig.height=7,fig.width=7-------------------------------------------
Rsp.out <- PlotRspBar(data=input, outcome.var="Response", binary=FALSE,
rsp.levels=c("CR", "PR","SD","NON CR/PD", "PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP")
## ------------------------------------------------------------------------
kable(Rsp.out$count,caption="count")
## ------------------------------------------------------------------------
kable(round(Rsp.out$perc,2), caption="percentage")
## ---- fig.height=7,fig.width=7-------------------------------------------
PlotRspBar(data=input, outcome.var="Response", binary=FALSE,
rsp.levels=c("CR", "PR","SD","NON CR/PD", "PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP", plot.count=TRUE)
## ---- fig.height=7,fig.width=7-------------------------------------------
Rsp.out.2 <- PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP")
## ------------------------------------------------------------------------
kable(Rsp.out.2$count,caption="count")
## ------------------------------------------------------------------------
kable(round(Rsp.out.2$perc,2), caption="percentage")
## ---- fig.height=7,fig.width=7-------------------------------------------
PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP", plot.count = TRUE)
## ---- fig.height=6,fig.width=8-------------------------------------------
input.ctrl <- subset(input, Arm=="CTRL") ## Data with only ctrl samples
res.multicut.ctrl <- PlotTabForestBiomarker(data=input.ctrl,
outcome.class=c("binary"),
outcome.var=c("Response"),
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="CTRL",
greater=TRUE, less=FALSE)
input.trt <- subset(input, Arm=="TRT") ## Data with only trt samples
res.multicut.trt <- PlotTabForestBiomarker(data=input.trt,
outcome.class=c("binary"),
outcome.var=c("Response"),
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="TRT",
greater=TRUE, less=FALSE)
## ---- fig.height=6,fig.width=10------------------------------------------
res.multicut.2arm <- PlotTabForestBiomarker(data=input,
outcome.class=c("binary"),
outcome.var=c("Response"),
trt = "Arm",
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE)
## ---- fig.height=6,fig.width=10------------------------------------------
res.multicut.2arm <- PlotTabForestBiomarker(data=input,
outcome.class=c("binary"),
outcome.var=c("Response"),
trt = "Arm",
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
within.bin=TRUE)
## ---- fig.height=7,fig.width=7-------------------------------------------
input$KRAS.exprs.2group <- ifelse(input$KRAS.exprs >= 100, ">=100","<100")
input$KRAS.exprs.2group <- factor(input$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
Rsp.out.2 <- PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
bep = "BEP",compare.var=TRUE, var="KRAS.exprs.2group")
## ---- fig.height=5,fig.width=7-------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input,
outcome.class="continuous",
outcome.var="Lab_ontrt",
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=TRUE, show.bep=TRUE)
## ------------------------------------------------------------------------
stepp.out <- PlotSTEPP(data = input,
outcome.var = "Lab_ontrt",
outcome.class = "continuous",
trt = "Arm",
var = "KRAS.exprs",
placebo.code = "CTRL",
active.code = "TRT"
)
## ---- message=FALSE------------------------------------------------------
head(longbmkr)
## ----longbmkr_description, message=FALSE, echo=FALSE---------------------
kable(
data.frame(
`Column Name` = names(longbmkr),
`English Name` = c("PatientID", "Treatment", "Sex", "Age", "Education", "Biomarker Measurement", "Visitation Month", "Endpoint Measurement"),
`Description` = c(
"Unique Patient Identifier",
"Binary Classification of Treatment (1) or Control (0)",
"Male (\"m\") or Female (\"f\") binary classification of sex",
"Age of Patient",
"Years of Education for the Patient",
"Biomarker Measurement|Mock Biomarker Measurement Reading",
"Timepoint that data was collected",
"Mock Endpoint Measurement Reading"
),
check.names = FALSE),
caption = "Longitudinal Biomarker Sample Data"
)
## ------------------------------------------------------------------------
baseline_data <- longbmkr[longbmkr['vm'] == 0,]
kable(
head(baseline_data),
caption = 'longitudinal data subset by visit month to produce baseline data'
)
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep)
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, fun.data = 'tukey',
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Tukey Whiskers and Hinges')
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, color=trt, fill=trt,
fun.data = 'tukey',
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = 'Ribbons represent Tukey hinges and whiskers')
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, group=trt, color=trt, fill=trt,
fun.data = 'tukey', facet.fun = . ~ sex,
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = 'Ribbons represent Tukey hinges and whiskers')
## ------------------------------------------------------------------------
library(dplyr)
## ---- fig.height = 5-----------------------------------------------------
cutoff = 1.5
longbmkr %>%
filter(vm <= 24) %>%
mutate(bmkr = ifelse(bmkr > cutoff, 'Positive', 'Negative')) %>%
mutate(trt = ifelse(trt == 0, 'CTRL', 'TRT')) %>%
PlotLong(x=vm, y=ep, color=trt, fill=trt, linetype=bmkr,
fun.data = 'mean_se',
show.counts = 'table',
plot.style = 'errorbars',
errorbar.linetype = 1,
xlab = 'Visitation Month',
ylab = 'Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = '*ribbons represent mean value +/- standard error of the mean.')
## ---- fig.height = 5-----------------------------------------------------
cutoff = 1.5
longbmkr %>%
filter(vm <= 24) %>%
mutate(bmkr = ifelse(bmkr > cutoff, 'Positive', 'Negative')) %>%
mutate(trt = ifelse(trt == 0, 'CTRL', 'TRT')) %>%
PlotLong(x=vm, y=ep, color=trt, fill=trt, linetype=bmkr,
model = lm,
model.formula = ep ~ sex + edu + age,
fun.data = 'mean_se',
show.counts = 'table',
plot.style = 'errorbars',
errorbar.linetype = 1,
xlab = 'Visitation Month',
ylab = 'Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = '*ribbons represent mean value +/- standard error of the mean.')
lengning/gClinBiomarker documentation built on May 9, 2019, 2:55 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
## ----setup, include=FALSE------------------------------------------------
if (!require(gClinBiomarker)) {
install_github("lengning/gClinBiomarker")
library(gClinBiomarker)
}
library(knitr)
## ---- warning=FALSE, message=FALSE, eval=FALSE---------------------------
# library(devtools)
# install_github("lengning/gClinBiomarker")
## ----warning=FALSE, message=FALSE, eval=FALSE----------------------------
# library(gClinBiomarker)
## ------------------------------------------------------------------------
head(input)
str(input)
## ------------------------------------------------------------------------
SummaryVars(data=input, trt='Arm', subgroup='BEP', var=c('Sex','Age'),
var.class=c('categorical','numeric'))
## ------------------------------------------------------------------------
kable(
SummaryVars(data=input, trt='Arm', subgroup='BEP', var=c('Sex','Age'),
var.class=c('categorical','numeric'))
)
## ---- fig.height=5, fig.width=10-----------------------------------------
CompareKM(data=input,tte='PFS', cen='PFS.event',trt='Arm', bep='BEP')
## ---- fig.height=7,fig.width=10------------------------------------------
PlotTabForestMulti(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var=c("Sex","Weight"),
bep="BEP",bep.indicator=1, compare.bep.itt=TRUE
)
## ------------------------------------------------------------------------
input.bep <- subset(input, BEP==1) # dataset with only BEP samples
kable(
CoxTab(data=input,tte="PFS", cens="PFS.event", var='Arm',
var.class="categorical"),
caption="full population, unadjusted"
)
kable(
CoxTab(data=input,tte="PFS", cens="PFS.event", var=c('Arm','Sex',"Weight"),
var.class=c("categorical","categorical","numeric")),
caption="full population, adjusted for Sex, Weight"
)
kable(
CoxTab(data=input.bep,tte="PFS", cens="PFS.event", var='Arm',
var.class="categorical"),
caption="BEP, unadjusted"
)
kable(
CoxTab(data=input.bep,tte="PFS", cens="PFS.event", var=c('Arm','Sex',"Weight"),
var.class=c("categorical","categorical","numeric")),
caption="BEP, adjusted for Sex, Weight"
)
## ----fig.width=12, fig.height=8------------------------------------------
PlotProperty(data=input, biomarker.var="KRAS.exprs", biomarker.class="numeric",
var=c("Sex", "Country"), var.class=c("categorical", "categorical"),
log2=TRUE, par.param = list(mfrow=c(2,3)))
## ----fig.width=8, fig.height=4-------------------------------------------
input.ctrl <- subset(input, Arm=="CTRL") ## Data with only ctrl samples
res.multicut.ctrl <- PlotTabForestBiomarker(data=input.ctrl,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="CTRL",
greater=TRUE, less=FALSE)
input.trt <- subset(input, Arm=="TRT") ## Data with only trt samples
res.multicut.trt <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="TRT",
greater=TRUE, less=FALSE)
## ---- fig.height=5,fig.width=10------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=5,fig.width=10------------------------------------------
res.withinbin <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
within.bin=TRUE,
show.itt=TRUE, show.bep=TRUE)
## ------------------------------------------------------------------------
stepp.out <- PlotSTEPP(data = input,
outcome.var = c("PFS", "PFS.event"),
outcome.class = "survival",
trt = "Arm",
var = "KRAS.exprs",
placebo.code = "CTRL",
active.code = "TRT"
)
## ---- fig.height=5,fig.width=8-------------------------------------------
res.subgroups.cut <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=NULL,
numerical.cutoff=100, within.bin=TRUE,
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=5,fig.width=10------------------------------------------
input$KRAS.exprs.2group <- ifelse(input$KRAS.exprs >= 100, ">=100","<100")
input$KRAS.exprs.2group <- factor(input$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
res.subgroups.bi <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.exprs.2group",
var.class="categorical",
show.itt=TRUE, show.bep=TRUE)
## ----include=TRUE,fig.width=9, fig.height=9------------------------------
PlotKM(data=input, tte="PFS",cen="PFS.event", bep="BEP",
main="PFS BEP by treatment, by KRAS expression subgroups",
var=c("Arm","KRAS.exprs.2group"), legend.loc="topright",
plot.median=TRUE)
## ------------------------------------------------------------------------
input.bep <- subset(input, BEP==1)
kable(
SummaryVars(data=input.bep,trt='Arm', subgroup='KRAS.exprs.2group', var=c('Sex'),
var.class="categorical", subgroup.indicator=">=100",compare.subgroup=TRUE, subgroup.name="exprs")
)
## ---- fig.height=7,fig.width=10------------------------------------------
res.subgroup.cov <- PlotTabForestMulti(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var=c("Sex","Weight"),
compare.bep.itt=FALSE,
compare.subgroup=TRUE,
subgroup="KRAS.exprs.2group"
)
## ------------------------------------------------------------------------
input.trt <- subset(input, Arm=="TRT")
## ------------------------------------------------------------------------
kable(
SummaryVars(data=input.trt, trt=NULL, subgroup='BEP', var=c('Age','Sex'),
var.class=c('numeric','categorical'))
)
## ---- fig.height=5, fig.width=5------------------------------------------
CompareKM(data=input.trt,tte='PFS', cen='PFS.event',trt=NULL, bep='BEP')
## ---- fig.height=7,fig.width=10------------------------------------------
PlotTabForestMulti(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var=c("Sex","Weight"),
bep="BEP",bep.indicator=1, compare.bep.itt=TRUE
)
## ------------------------------------------------------------------------
input.trt.bep <- subset(input.trt, BEP==1) # dataset with only BEP samples
kable(
CoxTab(data=input.trt,tte="PFS", cens="PFS.event", var=c('Sex',"Weight"),
var.class=c("categorical","numeric")),
caption="the full population, model of Sex, Weight"
)
kable(
CoxTab(data=input.trt.bep,tte="PFS", cens="PFS.event", var=c('Sex',"Weight"),
var.class=c("categorical","numeric")),
caption="BEP, model of Sex, Weight"
)
## ----fig.width=7, fig.height=4-------------------------------------------
PlotProperty(data=input.trt, biomarker.var="KRAS.exprs", biomarker.class="numeric",
var=c("Sex", "Country"), var.class=c("categorical", "categorical"),
log2=TRUE, par.param = list(mfrow=c(1,2)))
## ---- fig.height=5,fig.width=8-------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=FALSE, show.bep=FALSE)
## ---- fig.height=4,fig.width=8-------------------------------------------
res.subgroups.cut <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=NULL,
numerical.cutoff=100,
greater=TRUE,less=FALSE,
show.itt=FALSE, show.bep=FALSE)
## ---- fig.height=4,fig.width=9-------------------------------------------
input.trt$KRAS.exprs.trt.2group <- ifelse(input.trt$KRAS.exprs >= 100, ">=100","<100")
input.trt$KRAS.exprs.2group <- factor(input.trt$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
res.subgroups.bi <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.exprs.trt.2group",
var.class="categorical",
show.itt=FALSE, show.bep=FALSE)
## ----include=TRUE,fig.width=7, fig.height=7------------------------------
PlotKM(data=input.trt, tte="PFS",cen="PFS.event", bep="BEP",
main="PFS in BEP, by KRAS expression subgroups, single arm",
var=c("KRAS.exprs.trt.2group"), legend.loc="topright",
plot.median=TRUE)
## ------------------------------------------------------------------------
input.trt.bep <- subset(input.trt, BEP==1)
kable(
SummaryVars(data=input.trt.bep,trt=NULL, subgroup='KRAS.exprs.2group', var=c('Sex'),
var.class="categorical", subgroup.indicator=">=100",compare.subgroup=TRUE, subgroup.name="exprs")
)
## ---- fig.height=4,fig.width=9-------------------------------------------
res.subgroups.cat <- PlotTabForestBiomarker(data=input,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt="Arm",
var="KRAS.mutant",
var.class="categorical",
show.itt=TRUE, show.bep=TRUE)
## ---- fig.height=4,fig.width=9-------------------------------------------
res.subgroups.cat <- PlotTabForestBiomarker(data=input.trt,
outcome.class="survival",
outcome.var=c("PFS","PFS.event"),
trt=NULL,
var="KRAS.mutant",
var.class="categorical")
## ---- fig.height=7,fig.width=7-------------------------------------------
Rsp.out <- PlotRspBar(data=input, outcome.var="Response", binary=FALSE,
rsp.levels=c("CR", "PR","SD","NON CR/PD", "PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP")
## ------------------------------------------------------------------------
kable(Rsp.out$count,caption="count")
## ------------------------------------------------------------------------
kable(round(Rsp.out$perc,2), caption="percentage")
## ---- fig.height=7,fig.width=7-------------------------------------------
PlotRspBar(data=input, outcome.var="Response", binary=FALSE,
rsp.levels=c("CR", "PR","SD","NON CR/PD", "PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP", plot.count=TRUE)
## ---- fig.height=7,fig.width=7-------------------------------------------
Rsp.out.2 <- PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP")
## ------------------------------------------------------------------------
kable(Rsp.out.2$count,caption="count")
## ------------------------------------------------------------------------
kable(round(Rsp.out.2$perc,2), caption="percentage")
## ---- fig.height=7,fig.width=7-------------------------------------------
PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
compare.bep.itt=TRUE, bep = "BEP", plot.count = TRUE)
## ---- fig.height=6,fig.width=8-------------------------------------------
input.ctrl <- subset(input, Arm=="CTRL") ## Data with only ctrl samples
res.multicut.ctrl <- PlotTabForestBiomarker(data=input.ctrl,
outcome.class=c("binary"),
outcome.var=c("Response"),
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="CTRL",
greater=TRUE, less=FALSE)
input.trt <- subset(input, Arm=="TRT") ## Data with only trt samples
res.multicut.trt <- PlotTabForestBiomarker(data=input.trt,
outcome.class=c("binary"),
outcome.var=c("Response"),
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75), main.prefix="TRT",
greater=TRUE, less=FALSE)
## ---- fig.height=6,fig.width=10------------------------------------------
res.multicut.2arm <- PlotTabForestBiomarker(data=input,
outcome.class=c("binary"),
outcome.var=c("Response"),
trt = "Arm",
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE)
## ---- fig.height=6,fig.width=10------------------------------------------
res.multicut.2arm <- PlotTabForestBiomarker(data=input,
outcome.class=c("binary"),
outcome.var=c("Response"),
trt = "Arm",
rsp.cat = TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE",NA),
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
within.bin=TRUE)
## ---- fig.height=7,fig.width=7-------------------------------------------
input$KRAS.exprs.2group <- ifelse(input$KRAS.exprs >= 100, ">=100","<100")
input$KRAS.exprs.2group <- factor(input$KRAS.exprs.2group, levels=c(">=100","<100")) # ">=100" as Dx+
Rsp.out.2 <- PlotRspBar(data=input, outcome.var="Response", binary=TRUE,
rsp.response = c("CR","PR"),
rsp.nonresponse = c("SD", "PD","NON CR/PD","NE"),trt="Arm",
bep = "BEP",compare.var=TRUE, var="KRAS.exprs.2group")
## ---- fig.height=5,fig.width=7-------------------------------------------
res.multicut <- PlotTabForestBiomarker(data=input,
outcome.class="continuous",
outcome.var="Lab_ontrt",
trt="Arm",
var="KRAS.exprs",
var.class="numeric",
percentile.cutoff=c(.25,.5,.75),
greater=TRUE, less=FALSE,
show.itt=TRUE, show.bep=TRUE)
## ------------------------------------------------------------------------
stepp.out <- PlotSTEPP(data = input,
outcome.var = "Lab_ontrt",
outcome.class = "continuous",
trt = "Arm",
var = "KRAS.exprs",
placebo.code = "CTRL",
active.code = "TRT"
)
## ---- message=FALSE------------------------------------------------------
head(longbmkr)
## ----longbmkr_description, message=FALSE, echo=FALSE---------------------
kable(
data.frame(
`Column Name` = names(longbmkr),
`English Name` = c("PatientID", "Treatment", "Sex", "Age", "Education", "Biomarker Measurement", "Visitation Month", "Endpoint Measurement"),
`Description` = c(
"Unique Patient Identifier",
"Binary Classification of Treatment (1) or Control (0)",
"Male (\"m\") or Female (\"f\") binary classification of sex",
"Age of Patient",
"Years of Education for the Patient",
"Biomarker Measurement|Mock Biomarker Measurement Reading",
"Timepoint that data was collected",
"Mock Endpoint Measurement Reading"
),
check.names = FALSE),
caption = "Longitudinal Biomarker Sample Data"
)
## ------------------------------------------------------------------------
baseline_data <- longbmkr[longbmkr['vm'] == 0,]
kable(
head(baseline_data),
caption = 'longitudinal data subset by visit month to produce baseline data'
)
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep)
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, fun.data = 'tukey',
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Tukey Whiskers and Hinges')
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, color=trt, fill=trt,
fun.data = 'tukey',
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = 'Ribbons represent Tukey hinges and whiskers')
## ------------------------------------------------------------------------
PlotLong(longbmkr, x=vm, y=ep, group=trt, color=trt, fill=trt,
fun.data = 'tukey', facet.fun = . ~ sex,
xlab = 'Visitation Month',
ylab = 'Biomarker Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = 'Ribbons represent Tukey hinges and whiskers')
## ------------------------------------------------------------------------
library(dplyr)
## ---- fig.height = 5-----------------------------------------------------
cutoff = 1.5
longbmkr %>%
filter(vm <= 24) %>%
mutate(bmkr = ifelse(bmkr > cutoff, 'Positive', 'Negative')) %>%
mutate(trt = ifelse(trt == 0, 'CTRL', 'TRT')) %>%
PlotLong(x=vm, y=ep, color=trt, fill=trt, linetype=bmkr,
fun.data = 'mean_se',
show.counts = 'table',
plot.style = 'errorbars',
errorbar.linetype = 1,
xlab = 'Visitation Month',
ylab = 'Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = '*ribbons represent mean value +/- standard error of the mean.')
## ---- fig.height = 5-----------------------------------------------------
cutoff = 1.5
longbmkr %>%
filter(vm <= 24) %>%
mutate(bmkr = ifelse(bmkr > cutoff, 'Positive', 'Negative')) %>%
mutate(trt = ifelse(trt == 0, 'CTRL', 'TRT')) %>%
PlotLong(x=vm, y=ep, color=trt, fill=trt, linetype=bmkr,
model = lm,
model.formula = ep ~ sex + edu + age,
fun.data = 'mean_se',
show.counts = 'table',
plot.style = 'errorbars',
errorbar.linetype = 1,
xlab = 'Visitation Month',
ylab = 'Endpoint',
labs.title = 'Biomarker Timecourse',
labs.caption = '*ribbons represent mean value +/- standard error of the mean.')
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.