1 year ago
#377821
Rot Ger
problem deploying a perfectly working local shinyapp to the shinyapps website
i developed a shinyapp based on a research project i'm doing in my lab. i use Rstudio v3.6.3 and used the "DynNom" package to build a dynamic nomogram model to present our results. the model is based on a Cox proportional hazards regression model. the app works perfectly fine when i run it locally and also when i open it locally in my browser, yet when i try to publish it to my shinyapps account it doesn't work at all.
i tried uploading it both with the "rsconnect" package and via the built-in "publish" option. following a similar question here, i tried to reinstall the rsconnect package and even delete it completely from the folders containing the app. i also removed any absolute rather than relative paths that appeared in the code and completely deleted it. i reviewed the installed packages and chekced that all variables are found in the environment. still, with all these adaptations, the app worked perfectly locally and didn't work when published online.
thanks in advance!!
a reproducible code:
library(survival)
library(survminer)
library(ggplot2)
library(ggpubr)
library(DynNom)
library(rsconnect)
PC_data=subset(GBM_TME_full_031221[,c(2:5)])
idx=which(!rowSums(is.na((PC_data)))>0)
PC_data=PC_data[idx,]
PC_data=log10(PC_data*1000000+1)
PCA=prcomp(PC_data, scale. = TRUE)
PC1=PCA$x[,1]
PC2=PCA$x[,2]
comb_df <- cbind.data.frame(PC1, PC2, GBM_TME_full_031221[idx,c(10:14,18:31)])
idx1 <- which(comb_df$IDH=="V")
comb_df=comb_df[-idx1,]
comb_df <- comb_df[,-c(1,5,8,9:15,17:19,21)]
comb_df$AGE <- ifelse(comb_df$AGE>60,">60","<=60")
comb_df$ECOG <- ifelse(comb_df$ECOG>1, ">1","<=1")
comb_df$neuro_def <- as.factor(comb_df$neuro_def)
names(comb_df)[1] <-"lymph_score"
names(comb_df)[7] <-"percent_resected"
GBM_calc = coxph(Surv(time,event)~strata(AGE)+strata(ECOG)+strata(neuro_def)+lymph_score+percent_resected,data=comb_df)
GBM_calc_DynNom <- DynNom(model=GBM_calc, covariate="numeric", DNtitle = "newly-diagnosed wtIDH GBM calculator")
deployApp(appName = "GBM lymph_score survival calculator")
the shinyapp automatically produced by "DynNom" package. the code is as follows:
global:
library(ggplot2)
library(shiny)
library(plotly)
library(stargazer)
library(compare)
library(prediction)
library(survival)
load('data.RData')
source('functions.R')
m.summary <- 'raw'
covariate <- 'slider'
clevel <- 0.95
server:
server = function(input, output){
observe({if (input$quit == 1)
stopApp()})
output$manySliders <- renderUI({
slide.bars <- list()
for (j in 1:length(preds)){
if (preds[[j]]$dataClasses == "factor"){
slide.bars[[j]] <- list(selectInput(names(preds)[j], names(preds)[j], preds[[j]]$v.levels, multiple = FALSE))
}
if (preds[[j]]$dataClasses == "numeric"){
if (covariate == "slider") {
slide.bars[[j]] <- list(sliderInput(names(preds)[j], names(preds)[j],
min = preds[[j]]$v.min, max = preds[[j]]$v.max, value = preds[[j]]$v.mean))
}
if (covariate == "numeric") {
slide.bars[[j]] <- list(numericInput(names(preds)[j], names(preds)[j], value = zapsmall(preds[[j]]$v.mean, digits = 4)))
}}}
if (covariate == "slider") {
slide.bars[[length(preds) + 1]] <-
list(br(), checkboxInput("times", "Predicted Survival at this Follow Up:"),
conditionalPanel(condition = "input.times == true",
sliderInput("tim", tim[1], min = ttim$v.min, max = ttim$v.max, value = ttim$v.mean)))
} else {
slide.bars[[length(preds) + 1]] <-
list(br(), checkboxInput("times", "Predicted Survival at this Follow Up:"),
conditionalPanel(condition = "input.times == true",
numericInput("tim", tim[1], value = zapsmall(ttim$v.mean, digits = 4))))
}
do.call(tagList, slide.bars)
})
a <- 0
old.d <- NULL
new.d <- reactive({
input$add
input.v <- vector("list", length(preds) + 1)
input.v[[1]] <- isolate({ input[["tim"]] })
names(input.v)[1] <- tim[1]
for (i in 1:length(preds)) {
input.v[[i+1]] <- isolate({
input[[names(preds)[i]]]
})
names(input.v)[i+1] <- names(preds)[i]
}
out <- data.frame(lapply(input.v, cbind))
if (a == 0) {
wher <- match(names(out), names(input.data))
out <- out[wher]
input.data <<- rbind(input.data, out)
}
if (a > 0) {
wher <- match(names(out), names(input.data))
out <- out[wher]
if (!isTRUE(compare(old.d, out))) {
input.data <<- rbind(input.data, out)
}}
a <<- a + 1
out
})
p1 <- NULL
old.d <- NULL
data2 <- reactive({
if (input$add == 0)
return(NULL)
if (input$add > 0) {
if (!isTRUE(compare(old.d, new.d()))) {
OUT <- isolate({
new.d <- cbind(st.ind = 1, new.d())
names(new.d)[1] <- tim[2]
DNpred <- getpred.DN(model, new.d)
mpred <- DNpred$pred
se.pred <- DNpred$SEpred
pred <- mlinkF(mpred)
if (is.na(se.pred)) {
lwb <- NULL
upb <- NULL
} else {
lwb <- sort(mlinkF(mpred + cbind(1, -1) * (qnorm(1 - (1 - clevel)/2) * se.pred)))[1]
upb <- sort(mlinkF(mpred + cbind(1, -1) * (qnorm(1 - (1 - clevel)/2) * se.pred)))[2]
if (upb > 1) {
upb <- 1
}}
if (ptype == "st") {
d.p <- data.frame(Prediction = zapsmall(pred, digits = 2),
Lower.bound = zapsmall(lwb, digits = 2),
Upper.bound = zapsmall(upb, digits = 2))
}
if (ptype == "1-st") {
d.p <- data.frame(Prediction = zapsmall(1-pred, digits = 2),
Lower.bound = zapsmall(1-upb, digits = 2),
Upper.bound = zapsmall(1-lwb, digits = 2))
}
old.d <<- new.d[,-1]
data.p <- cbind(d.p, counter = TRUE)
if (DNpred$InRange){
p1 <<- rbind(p1[,-5], data.p)
} else{
p1 <<- rbind(p1[,-5], data.frame(Prediction = NA, Lower.bound = NA, Upper.bound = NA, counter = FALSE))
}
p1
})
} else {
p1$count <- seq(1, dim(p1)[1])
}}
p1
})
s.fr <- NULL
old.d2 <- NULL
b <- 1
dat.p <- reactive({
if (isTRUE(compare(old.d2, new.d())) == FALSE) {
try.survfit <- !any(class(try(survfit(model, newdata = new.d()), silent = TRUE)) == "try-error")
if (try.survfit){
fit1 <- survfit(model, newdata = new.d())
}
if (n.strata == 0) {
sff <- data.frame(summary(fit1)[c("time", "n.risk", "surv")])
sff <- cbind(sff, event=1-sff$surv, part = b)
if (sff$time[1] != 0){
sff <- rbind(data.frame(time=0, n.risk=sff$n.risk[1] ,surv=1, event=0, part=sff$part[1]), sff)
}}
if (n.strata > 0) {
nam <- NULL
new.sub <- T
for (i in 1:(dim.terms-1)) {
if (preds[[i]]$dataClasses == "factor"){
if (preds[[i]]$IFstrata){
nam0=paste(new.d()[[names(preds[i])]], sep = '')
if (new.sub) {
nam <- paste(nam0)
new.sub <- F
} else {
nam <- paste(nam, ', ', nam0, sep = '')
}}}}
if (try.survfit){
sub.fit1 <- subset(as.data.frame(summary(fit1)[c("time", "n.risk", "strata", "surv")]), strata == nam)
} else{
sub.fit1 <- data.frame(time=NA, n.risk=NA, strata=NA, surv=NA, event=NA, part=NA)[0,]
}
if (!try.survfit){
message("The strata levels not found in the original")
sff <- cbind(sub.fit1, event=NULL, part = NULL)
b <<- b - 1
} else{
sff <- cbind(sub.fit1, event=1-sub.fit1$surv, part = b)
if (sff$time[1] != 0) {
sff <- rbind(data.frame(time=0, n.risk=sff$n.risk[1], strata=sff$strata[1] ,surv=1, event=0, part=sff$part[1]), sff)
}
sff$n.risk <- sff$n.risk/sff$n.risk[1]
}
sff$n.risk <- sff$n.risk/sff$n.risk[1]
}
s.fr <<- rbind(s.fr, sff)
old.d2 <<- new.d()
b <<- b + 1
}
s.fr
})
dat.f <- reactive({
if (nrow(data2() > 0))
cbind(input.data, data2()[1:3])
})
# KM plot
output$plot <- renderPlot({
data2()
if (input$add == 0)
return(NULL)
if (input$add > 0) {
if (ptype == "st") {
if (input$trans == TRUE) {
pl <- ggplot(data = dat.p()) +
geom_step(aes(x = time, y = surv, alpha = n.risk, group = part), color = coll[dat.p()$part])
}
if (input$trans == FALSE) {
pl <- ggplot(data = dat.p()) +
geom_step(aes(x = time, y = surv, group = part), color = coll[dat.p()$part])
}}
if (ptype == "1-st") {
if (input$trans == TRUE) {
pl <- ggplot(data = dat.p()) +
geom_step(aes(x = time, y = event, alpha = n.risk, group = part), color = coll[dat.p()$part])
}
if (input$trans == FALSE) {
pl <- ggplot(data = dat.p()) +
geom_step(aes(x = time, y = event, group = part), color = coll[dat.p()$part])
}}
pl <- pl + ylim(0, 1) + xlim(0, max(dat.p()$time) * 1.05) +
labs(title = "Probability of indolent disease course", x = "Follow Up Time", y = "S(t)") + theme_bw() +
theme(text = element_text(face = "bold", size = 12), legend.position = "none", plot.title = element_text(hjust = .5))
}
print(pl)
})
output$plot2 <- renderPlotly({
if (input$add == 0)
return(NULL)
if (is.null(new.d()))
return(NULL)
lim <- c(0, 1)
yli <- c(0 - 0.5, 10 + 0.5)
input.data = input.data[data2()$counter,]
in.d <- data.frame(input.data)
xx=matrix(paste(names(in.d), ": ",t(in.d), sep=""), ncol=dim(in.d)[1])
text.cov=apply(xx,2,paste,collapse="<br />")
if (dim(input.data)[1] > 11)
yli <- c(dim(input.data)[1] - 11.5, dim(input.data)[1] - 0.5)
dat2 <- data2()[data2()$counter,]
dat2$count = seq(1, nrow(dat2))
p <- ggplot(data = dat2, aes(x = Prediction, y = count - 1, text = text.cov,
label = Prediction, label2 = Lower.bound, label3=Upper.bound)) +
geom_point(size = 2, colour = coll[dat2$count], shape = 15) +
ylim(yli[1], yli[2]) + coord_cartesian(xlim = lim) +
labs(title = "95% Confidence Interval for Response",
x = "Survival probability", y = "") + theme_bw() +
theme(axis.text.y = element_blank(), text = element_text(face = "bold", size = 10))
if (is.numeric(dat2$Upper.bound)){
p <- p + geom_errorbarh(xmax = dat2$Upper.bound, xmin = dat2$Lower.bound,
size = 1.45, height = 0.4, colour = coll[dat2$count])
} else{
message("Confidence interval is not available as there is no standard errors available by 'coxph' ")
}
if (ptype == "st") {
p <- p + labs(title = paste(clevel * 100, "% ", "Confidence Interval for Survival Probability", sep = ""),
x = DNxlab, y = DNylab)
}
if (ptype == "1-st") {
p <- p + labs(title = paste(clevel * 100, "% ", "Confidence Interval for F(t)", sep = ""),
x = DNxlab, y = DNylab)
}
gp=ggplotly(p, tooltip = c("text","label","label2","label3"))
gp$elementId <- NULL
dat.p()
gp
})
output$data.pred <- renderPrint({
if (input$add > 0) {
if (nrow(data2() > 0)) {
stargazer(dat.f(), summary = FALSE, type = "text")
}}
})
output$summary <- renderPrint({
summary(model)
})
}
ui:
ui = bootstrapPage(fluidPage(
titlePanel('survival prediction for newly-diagnosed wtIDH GBM'),
sidebarLayout(sidebarPanel(uiOutput('manySliders'),
checkboxInput('trans', 'Alpha blending (transparency)', value = TRUE),
actionButton('add', 'Predict'),
br(), br(),
helpText('Press Quit to exit the application'),
actionButton('quit', 'Quit')
),
mainPanel(tabsetPanel(id = 'tabs',
tabPanel('Survival plot', plotOutput('plot')),
tabPanel('Predicted Survival', plotlyOutput('plot2')),
tabPanel('Numerical Summary', verbatimTextOutput('data.pred')),
tabPanel('Model Summary', verbatimTextOutput('summary'))
)
)
)))
when trying to publish there is an error stating:An error has occurred. Check your logs or contact the app author for clarification.
i tried checking the logs:
2022-04-05T13:50:09.289730+00:00 shinyapps[6016455]: Warning: namespace ‘ggfortify’ is not available and has been replaced
2022-04-05T13:50:09.289782+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘all_BTS_4M_PCA_plot’
2022-04-05T13:50:09.289885+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘multiparameteric_tree’
2022-04-05T13:50:09.289835+00:00 shinyapps[6016455]: Warning: namespace ‘modeltools’ is not available and has been replaced
2022-04-05T13:50:09.289930+00:00 shinyapps[6016455]: Warning: namespace ‘party’ is not available and has been replaced
2022-04-05T13:50:09.289977+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘multiparameteric_tree’
2022-04-05T13:50:09.290021+00:00 shinyapps[6016455]: Warning: namespace ‘cowplot’ is not available and has been replaced
2022-04-05T13:50:09.290067+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘PT_PCA_4M_vs_comb’
2022-04-05T13:50:10.289863+00:00 shinyapps[6016455]: LANG: C.UTF-8
2022-04-05T13:50:10.289941+00:00 shinyapps[6016455]: Working directory: /srv/connect/apps/GBM_survival_DynNomApp
2022-04-05T13:50:10.289750+00:00 shinyapps[6016455]: Running on host: 55429d02f485
2022-04-05T13:50:10.289988+00:00 shinyapps[6016455]: R version: 3.6.3
2022-04-05T13:50:10.289806+00:00 shinyapps[6016455]: Server version: 2022.03.1
2022-04-05T13:50:10.290040+00:00 shinyapps[6016455]: shiny version: 1.5.0
2022-04-05T13:50:10.290231+00:00 shinyapps[6016455]: jsonlite version: 1.7.2
2022-04-05T13:50:10.290285+00:00 shinyapps[6016455]: RJSONIO version: (none)
2022-04-05T13:50:10.290186+00:00 shinyapps[6016455]: knitr version: (none)
2022-04-05T13:50:10.290135+00:00 shinyapps[6016455]: rmarkdown version: (none)
2022-04-05T13:50:10.290089+00:00 shinyapps[6016455]: httpuv version: 1.5.4
2022-04-05T13:50:10.290392+00:00 shinyapps[6016455]: htmltools version: 0.5.0
2022-04-05T13:50:10.290461+00:00 shinyapps[6016455]: reticulate version: (none)
2022-04-05T13:50:10.290515+00:00 shinyapps[6016455]: Using pandoc: /opt/connect/ext/pandoc/2.16
2022-04-05T13:50:10.290737+00:00 shinyapps[6016455]: Shiny application starting ...
2022-04-05T13:50:10.290816+00:00 shinyapps[6016455]: Attaching package: ‘plotly’
2022-04-05T13:50:10.290610+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.290693+00:00 shinyapps[6016455]: Starting R with process ID: '25'
2022-04-05T13:50:10.290778+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.290563+00:00 shinyapps[6016455]: Using jsonlite for JSON processing
2022-04-05T13:50:10.290898+00:00 shinyapps[6016455]: The following object is masked from ‘package:ggplot2’:
2022-04-05T13:50:10.290852+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.290940+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291032+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.290984+00:00 shinyapps[6016455]: last_plot
2022-04-05T13:50:10.291077+00:00 shinyapps[6016455]: The following object is masked from ‘package:stats’:
2022-04-05T13:50:10.291120+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291188+00:00 shinyapps[6016455]: filter
2022-04-05T13:50:10.291247+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291461+00:00 shinyapps[6016455]: layout
2022-04-05T13:50:10.291293+00:00 shinyapps[6016455]: The following object is masked from ‘package:graphics’:
2022-04-05T13:50:10.291354+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291533+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291603+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291670+00:00 shinyapps[6016455]: Please cite as:
2022-04-05T13:50:10.291727+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291798+00:00 shinyapps[6016455]: Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
2022-04-05T13:50:10.291871+00:00 shinyapps[6016455]: R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
2022-04-05T13:50:10.291927+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.291994+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.292072+00:00 shinyapps[6016455]: Attaching package: ‘compare’
2022-04-05T13:50:10.292142+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.292218+00:00 shinyapps[6016455]: The following object is masked from ‘package:base’:
2022-04-05T13:50:10.292293+00:00 shinyapps[6016455]:
2022-04-05T13:50:10.292382+00:00 shinyapps[6016455]: isTRUE
2022-04-05T13:50:10.292446+00:00 shinyapps[6016455]:
2022-04-05T13:50:11.311435+00:00 shinyapps[6016455]: Warning: namespace ‘DynNom’ is not available and has been replaced
2022-04-05T13:50:11.311507+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘model’
2022-04-05T13:50:11.311559+00:00 shinyapps[6016455]:
2022-04-05T13:50:11.311638+00:00 shinyapps[6016455]: Listening on http://127.0.0.1:43869
2022-04-05T13:50:25.309733+00:00 shinyapps[6016455]: Warning: namespace ‘ggfortify’ is not available and has been replaced
2022-04-05T13:50:25.309789+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘all_BTS_4M_PCA_plot’
2022-04-05T13:50:26.289762+00:00 shinyapps[6016455]: Warning: namespace ‘modeltools’ is not available and has been replaced
2022-04-05T13:50:26.289820+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘multiparameteric_tree’
2022-04-05T13:50:26.289869+00:00 shinyapps[6016455]: Warning: namespace ‘party’ is not available and has been replaced
2022-04-05T13:50:26.289918+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘multiparameteric_tree’
2022-04-05T13:50:26.289976+00:00 shinyapps[6016455]: Warning: namespace ‘cowplot’ is not available and has been replaced
2022-04-05T13:50:26.290024+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘PT_PCA_4M_vs_comb’
2022-04-05T13:50:26.290161+00:00 shinyapps[6016455]: LANG: C.UTF-8
2022-04-05T13:50:26.290075+00:00 shinyapps[6016455]: Running on host: 55429d02f485
2022-04-05T13:50:26.290115+00:00 shinyapps[6016455]: Server version: 2022.03.1
2022-04-05T13:50:26.290243+00:00 shinyapps[6016455]: R version: 3.6.3
2022-04-05T13:50:26.290202+00:00 shinyapps[6016455]: Working directory: /srv/connect/apps/GBM_survival_DynNomApp
2022-04-05T13:50:26.290285+00:00 shinyapps[6016455]: shiny version: 1.5.0
2022-04-05T13:50:26.290325+00:00 shinyapps[6016455]: httpuv version: 1.5.4
2022-04-05T13:50:26.290424+00:00 shinyapps[6016455]: knitr version: (none)
2022-04-05T13:50:26.290590+00:00 shinyapps[6016455]: htmltools version: 0.5.0
2022-04-05T13:50:26.290381+00:00 shinyapps[6016455]: rmarkdown version: (none)
2022-04-05T13:50:26.290469+00:00 shinyapps[6016455]: jsonlite version: 1.7.2
2022-04-05T13:50:26.290542+00:00 shinyapps[6016455]: RJSONIO version: (none)
2022-04-05T13:50:26.290684+00:00 shinyapps[6016455]: Using pandoc: /opt/connect/ext/pandoc/2.16
2022-04-05T13:50:26.290735+00:00 shinyapps[6016455]: Using jsonlite for JSON processing
2022-04-05T13:50:26.290821+00:00 shinyapps[6016455]: Starting R with process ID: '44'
2022-04-05T13:50:26.290640+00:00 shinyapps[6016455]: reticulate version: (none)
2022-04-05T13:50:26.290776+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.290917+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.290874+00:00 shinyapps[6016455]: Shiny application starting ...
2022-04-05T13:50:26.290958+00:00 shinyapps[6016455]: Attaching package: ‘plotly’
2022-04-05T13:50:26.290988+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291026+00:00 shinyapps[6016455]: The following object is masked from ‘package:ggplot2’:
2022-04-05T13:50:26.291076+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291170+00:00 shinyapps[6016455]: last_plot
2022-04-05T13:50:26.291305+00:00 shinyapps[6016455]: The following object is masked from ‘package:stats’:
2022-04-05T13:50:26.291230+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291365+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291429+00:00 shinyapps[6016455]: filter
2022-04-05T13:50:26.291495+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291553+00:00 shinyapps[6016455]: The following object is masked from ‘package:graphics’:
2022-04-05T13:50:26.291606+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291665+00:00 shinyapps[6016455]: layout
2022-04-05T13:50:26.291723+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291778+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291835+00:00 shinyapps[6016455]: Please cite as:
2022-04-05T13:50:26.291896+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.291958+00:00 shinyapps[6016455]: Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.
2022-04-05T13:50:26.292015+00:00 shinyapps[6016455]: R package version 5.2.2. https://CRAN.R-project.org/package=stargazer
2022-04-05T13:50:26.292078+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.292130+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.292190+00:00 shinyapps[6016455]: Attaching package: ‘compare’
2022-04-05T13:50:26.292247+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.292308+00:00 shinyapps[6016455]: The following object is masked from ‘package:base’:
2022-04-05T13:50:26.292361+00:00 shinyapps[6016455]:
2022-04-05T13:50:26.292418+00:00 shinyapps[6016455]: isTRUE
2022-04-05T13:50:26.292478+00:00 shinyapps[6016455]:
2022-04-05T13:50:27.326666+00:00 shinyapps[6016455]: Warning: namespace ‘DynNom’ is not available and has been replaced
2022-04-05T13:50:27.326726+00:00 shinyapps[6016455]: by .GlobalEnv when processing object ‘model’
2022-04-05T13:50:27.326788+00:00 shinyapps[6016455]:
2022-04-05T13:50:27.326851+00:00 shinyapps[6016455]: Listening on http://127.0.0.1:46637
2022-04-05T13:50:30.289739+00:00 shinyapps[6016455]: Warning: Error in $: $ operator is invalid for atomic vectors
2022-04-05T13:50:30.289803+00:00 shinyapps[6016455]: 110: renderUI [/srv/connect/apps/GBM_survival_DynNomApp/server.R#8]
2022-04-05T13:50:30.289914+00:00 shinyapps[6016455]: 96: origRenderFunc
2022-04-05T13:50:30.289855+00:00 shinyapps[6016455]: 109: func
2022-04-05T13:50:30.289968+00:00 shinyapps[6016455]: 95: output$manySliders
2022-04-05T13:50:30.290017+00:00 shinyapps[6016455]: 15: <Anonymous>
2022-04-05T13:50:30.290104+00:00 shinyapps[6016455]: 8: retry
2022-04-05T13:50:30.290057+00:00 shinyapps[6016455]: 13: fn
2022-04-05T13:50:30.290150+00:00 shinyapps[6016455]: 7: connect$retryingStartServer
2022-04-05T13:50:30.290187+00:00 shinyapps[6016455]: 6: eval
2022-04-05T13:50:30.290220+00:00 shinyapps[6016455]: 5: eval
r
shinyapps
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