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app.R
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app.R
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# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# SuperPlotsOfData: Shiny app for plotting and comparing data from different replicates
# Created by Joachim Goedhart (@joachimgoedhart), first version 2020
# Uses tidy data as input with a column that defines conditions and a column with measured values
# A third column can be selected that indicates the replicates (as numbers or other unique strings)
# Raw data is displayed with user-defined visibility (alpha)
# Summary statistics are displayed with user-defined visibility (alpha)
# A plot and a table with stats are generated
# Several colorblind safe palettes are available
# Ordering of the conditions is 'as is', based on median or alphabetical
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Copyright (C) 2020 Joachim Goedhart
# electronic mail address: j #dot# goedhart #at# uva #dot# nl
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
# ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Improvements:
# display of p-values (use of scientific notation if smaller than 0.001
# Needs fixing, since doesn't work for multiple conditions)
# Implement measures of reproducibility/repeatability
library(shiny)
library(plyr)
library(tidyverse)
library(ggbeeswarm)
library(readxl)
library(DT)
library(RCurl)
library(broom)
#Uncomment for sinaplot
#library(ggforce)
source("geom_flat_violin.R")
source("themes.R")
source("function_tidy_df.R")
source("repeatability.R")
###### Functions ##########
# Function that returns the p-value from Shapiro-Wilk test
f = function(x){
if (length(x)<3) {return(NA)}
# Return NA in case all numbers are identical
if (length(unique(x))<2) {return(NA)}
st = shapiro.test(x)
return(st$p.value)
}
#Custom stats for ggplot2: https://stackoverflow.com/questions/6717675/how-can-one-write-a-function-to-create-custom-error-bars-for-use-with-ggplot2/6717697
add_SD <- function(x) {
avg <- mean(x)
sd <- sd(x)
triplet <- data.frame(avg, avg-sd, avg+sd)
names(triplet) <- c("y","ymin","ymax") #this is what ggplot is expecting
return (triplet)
}
add_CI <- function(x) {
avg <- mean(x)
sd <- sd(x)
n <- length(x)
sem <- sd / sqrt(n - 1)
CI_lo = avg + qt((1-0.95)/2, n - 1) * sem
CI_hi = avg - qt((1-0.95)/2, n - 1) * sem
triplet <- data.frame(avg, CI_lo, CI_hi)
names(triplet) <- c("y","ymin","ymax") #this is what ggplot is expecting
return (triplet)
}
add_sem <- function(x) {
avg <- mean(x)
sd <- sd(x)
n <- length(x)
sem <- sd / sqrt(n - 1)
triplet <- data.frame(avg, avg-sem, avg+sem)
names(triplet) <- c("y","ymin","ymax") #this is what ggplot is expecting
return (triplet)
}
##### Global variables #####
i=0
#Number of bootstrap samples
nsteps=1000
#Confidence level
Confidence_Percentage = 95
Confidence_level = Confidence_Percentage/100
alpha=1-Confidence_level
lower_percentile=(1-Confidence_level)/2
upper_percentile=1-((1-Confidence_level)/2)
#Code to generate vectors in R to use these palettes
#From Paul Tol: https://personal.sron.nl/~pault/
Tol_bright <- c('#EE6677', '#228833', '#4477AA', '#CCBB44', '#66CCEE', '#AA3377', '#BBBBBB')
Tol_muted <- c('#88CCEE', '#44AA99', '#117733', '#332288', '#DDCC77', '#999933','#CC6677', '#882255', '#AA4499', '#DDDDDD')
Tol_light <- c('#BBCC33', '#AAAA00', '#77AADD', '#EE8866', '#EEDD88', '#FFAABB', '#99DDFF', '#44BB99', '#DDDDDD')
Greyscale <- c('grey30','grey40','grey50','grey60','grey70')
#From Color Universal Design (CUD): https://jfly.uni-koeln.de/color/
Okabe_Ito <- c("#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#000000")
#Read a text file (comma separated values)
df_tidy_example <- read.csv("combined.csv", na.strings = "", stringsAsFactors = TRUE)
df_tidy_example2 <- read.csv("SystBloodPressure_tidy.csv", na.strings = "", stringsAsFactors = TRUE)
# Create a reactive object here that we can share between all the sessions.
vals <- reactiveValues(count=0)
###### UI: User interface #########
ui <- fluidPage(
titlePanel("SuperPlotsOfData - Plots Data and its Replicates"),
sidebarLayout(
sidebarPanel(width=3,
conditionalPanel(
condition = "input.tabs=='Data upload'",
radioButtons(
"data_input", h4("Data upload"),
choices =
list(
# "Example data (tidy format)" = 1,
"Example data (tidy)" = 1,
"Example data (tidy)" = 2,
"Upload file" = 3,
"Paste data" = 4,
"URL (csv files only)" = 5
)
,
selected = 1),
conditionalPanel(
condition = "input.data_input=='2'"
),
conditionalPanel(
condition = "input.data_input=='1'",
p("Data S1 published in the original SuperPlots paper:"),a("https://doi.org/10.1083/jcb.202001064", href="https://doi.org/10.1083/jcb.202001064")
),
conditionalPanel(
condition = "input.data_input=='2'",
p("Data from Table 1 of:"),a("Bland & Altman (1999)", href="https://doi.org/10.1177/096228029900800204")
),
conditionalPanel(
condition = "input.data_input=='3'",
h5("Upload file: "),
fileInput("upload", NULL, multiple = FALSE, accept = c(".xlsx", ".xls", ".txt", ".csv")),
# selectInput("file_type", "Type of file:",
# list("text (csv)" = "text",
# "Excel" = "Excel"
# ),
# selected = "text"),
selectInput("upload_delim", label = "Select Delimiter (for text file):", choices =list("Comma" = ",",
"Tab" = "\t",
"Semicolon" = ";",
"Space" = " "))),
# selectInput("sheet", label = "Select sheet (for excel workbook):", choices = " "),
# conditionalPanel(
# condition = "input.file_type=='text'",
#
# radioButtons(
# "upload_delim", "Delimiter",
# choices =
# list("Comma" = ",",
# "Tab" = "\t",
# "Semicolon" = ";",
# "Space" = " "),
# selected = ",")),
#
# actionButton("submit_datafile_button",
# "Submit datafile")),
conditionalPanel(
condition = "input.data_input=='4'",
h5("Paste data below:"),
tags$textarea(id = "data_paste",
placeholder = "Add data here",
rows = 10,
cols = 20, ""),
actionButton("submit_data_button", "Submit data"),
radioButtons(
"text_delim", "Delimiter",
choices =
list("Tab (from Excel)" = "\t",
"Space" = " ",
"Comma" = ",",
"Semicolon" = ";"),
selected = "\t")),
### csv via URL as input
conditionalPanel(
condition = "input.data_input=='5'",
# textInput("URL", "URL", value = "https://zenodo.org/record/2545922/files/FRET-efficiency_mTq2.csv"),
textInput("URL", "URL", value = ""),
NULL
),
hr(),
h4('Data conversion'),
checkboxInput(inputId = "toggle_tidy", label = "Convert to tidy", value = FALSE),
conditionalPanel(
condition = "input.toggle_tidy==true",
########### Ask for number of rows and labels (optional) ############
numericInput("n_conditions", "Number of rows that specify parameters:", value = 1,min = 1,max=10,step = 1),
textInput("labels", "Labels for parameters (separated by comma):", value = ""),
NULL),
hr(),
h4('Data selection for plotting'),
selectInput("x_var", "Data for the x-axis:", choices = "Treatment", selected="Treatment"),
selectInput("y_var", "Data for the y-axis:", choices = "Speed", selected="Speed"),
selectInput("g_var", "Groups/Replicates:", choices = list("Replicate", "-"), selected="Replicate"),
hr(),
# selectInput("filter_column", "Filter based on this parameter:", choices = ""),
selectInput("use_these_conditions", "Select and order:", "", multiple = TRUE),
hr(),
h4('Data properties'),
checkboxInput(inputId = "x_cont",
label = "Continuous x-axis data",
value = FALSE),
checkboxInput(inputId = "paired",
label = "All data are paired/connected",
value = FALSE),
hr(),
checkboxInput(inputId = "info_data",
label = "Show information on data formats",
value = FALSE),
conditionalPanel(
condition = "input.info_data==true",
p("The data has to be organized in a 'tidy' format. This means that all measured values must be present in a single column ('Speed' in the example data). The labels for the conditions are present in another column ('Treatment' in the example data). When different replicates are present, this information is stored in a third column ('Replicate' in the example data). The selection of a column with replicates is optional. The order of the columns is arbitrary. For more information, see:"),
a("A tutorial on preparing data for superplots", href = "https://thenode.biologists.com/converting-excellent-spreadsheets-part2"),br(),
a("A basic intro on converting spreadsheet data", href = "http://thenode.biologists.com/converting-excellent-spreadsheets-tidy-data/education/"),br(),
a("The original paper by Hadley Wickham 'Tidy data'", href = "http://dx.doi.org/10.18637/jss.v059.i10")
),
NULL
),
conditionalPanel(
condition = "input.tabs=='Plot'",
radioButtons(inputId = "jitter_type", label = h4("Data display"), choices = list("Data & distribution" = "quasirandom", "Jittered data" = "random","No offset"="no_jitter", "Distribution only"="violin"), selected = "quasirandom"),
checkboxInput(inputId = "change_size", label = "Change size", value = FALSE),
conditionalPanel(condition = "input.change_size == true",
numericInput("dot_size", "Size:", value = 3.5),
),
sliderInput(inputId = "alphaInput", label = "Visibility of the data", 0, 1, 0.7),
h4("Replicates"),
radioButtons(inputId = "summary_replicate", label = "Statistics per replicate:", choices = list("Mean" = "mean", "Median" = "median"), selected = "mean"),
sliderInput(inputId = "alphaStats", label = "Visibility of the stats", 0, 1, 1),
radioButtons(inputId = "connect", label = "Connect the dots (treat as paired data):", choices = list("No" = "blank", "Dotted line" = "dotted", "Dashed line"= "dashed", "Solid line" ="solid"), selected = "blank"),
# checkboxInput(inputId = "connect", label = "Connect the dots (paired data)", FALSE),
# conditionalPanel(condition = "input.connect == true",
# checkboxInput(inputId = "solid", label = "Solid line", FALSE)
# ),
#
checkboxInput(inputId = "add_shape", label = "Identify by shape", value = FALSE),
checkboxInput(inputId = "add_n", label = "Size reflects 'n' (new feature)", value = FALSE),
checkboxInput(inputId = "show_distribution", label = "Distribution per replicate", value = FALSE),
radioButtons("adjustcolors", "By color:",
choices =
list("Greyscale" = 1,
"Viridis" = 2,
"Okabe&Ito; CUD" = 6,
"Tol; bright" = 3,
"Tol; light" = 4,
"User defined"=5),
selected = 6),
conditionalPanel(condition = "input.adjustcolors == 5",
textInput("user_color_list", "Names or hexadecimal codes separated by a comma (applied to conditions in alphabetical order):", value = "turquoise2,#FF2222,lawngreen"),
h5("",a("Click here for more info on color names", href = "http://www.endmemo.com/program/R/color.php", target="_blank"))
),
selectInput("split_direction", label = "Split replicates:", choices = list("No", "Horizontal", "Vertical"), selected = "No"),
# h4("Comparing conditions"),
radioButtons(inputId = "summary_condition", label = "Error bars:", choices = list("Mean & S.D." = "mean_SD", "Mean & 95%CI" = "mean_CI", "Mean & s.e.m." = "mean_sem", "none"="none"), selected = "none"),
conditionalPanel(condition = "input.summary_condition != 'none'",
sliderInput("alphaInput_summ", "Visibility of the error bar:", 0, 1, 1)
),
checkboxInput(inputId = "show_table", label = "Table with quantitative comparison", value = FALSE),
# conditionalPanel(condition = "input.show_table == true",
selectInput("zero", "Select reference condition:", choices = ""
# )
),
h4("Plot Layout"),
radioButtons(inputId = "ordered", label= "Order of the conditions:", choices = list("As supplied" = "none", "By median value" = "median", "By alphabet/number" = "alphabet"), selected = "none"),
checkboxInput(inputId = "rotate_plot", label = "Rotate plot 90 degrees", value = FALSE),
checkboxInput(inputId = "no_grid", label = "Remove gridlines", value = FALSE),
checkboxInput(inputId = "change_scale", label = "Change scale", value = FALSE),
conditionalPanel(condition = "input.change_scale == true", checkboxInput(inputId = "scale_log_10", label = "Log scale", value = FALSE),
textInput("range", "Range of values (min,max)", value = "")),
# checkboxInput(inputId = "add_CI", label = HTML("Add 95% CI <br/> (minimum n=10)"), value = FALSE),
# conditionalPanel(
# condition = "input.add_CI == true && input.summary_replicate !='box'",
# checkboxInput(inputId = "ugly_errors", label = "Classic error bars", value = FALSE)),
########## Choose color from list
# selectInput("colour_list", "Colour:", choices = ""),
checkboxInput(inputId = "dark", label = "Dark Theme", value = FALSE),
# conditionalPanel(
# condition = "input.dark == true",checkboxInput(inputId = "dark_classic", label = "Classic Dark Theme", value = FALSE)),
numericInput("plot_height", "Height (# pixels): ", value = 480),
numericInput("plot_width", "Width (# pixels):", value = 480),
h4("Labels/captions"),
checkboxInput(inputId = "add_title",
label = "Add title",
value = FALSE),
conditionalPanel(
condition = "input.add_title == true",
textInput("title", "Title:", value = "")
),
checkboxInput(inputId = "label_axes",
label = "Change labels",
value = FALSE),
conditionalPanel(
condition = "input.label_axes == true",
textInput("lab_x", "X-axis:", value = ""),
textInput("lab_y", "Y-axis:", value = "")),
checkboxInput(inputId = "adj_fnt_sz",
label = "Change font size",
value = FALSE),
conditionalPanel(
condition = "input.adj_fnt_sz == true",
numericInput("fnt_sz_title", "Plot title:", value = 24),
numericInput("fnt_sz_labs", "Axis titles:", value = 24),
numericInput("fnt_sz_ax", "Axis labels:", value = 18)
),
checkboxInput(inputId = "add_legend",
label = "Add legend",
value = FALSE),
NULL
),
conditionalPanel(
condition = "input.tabs=='About'",
#Session counter: https://gist.github.com/trestletech/9926129
h4("About"), "There are currently",
verbatimTextOutput("count"),
"session(s) connected to this app.",
hr(),
h4("Find our other dataViz apps at:"),a("https://huygens.science.uva.nl/", href = "https://huygens.science.uva.nl/")
),
conditionalPanel(
condition = "input.tabs=='Data Summary'",
h4("Data summary") ,
# checkboxGroupInput("stats_select", label = h5("Statistics for replicates:"),
# choices = list("mean", "sd", "sem","95CI mean", 'p(Shapiro-Wilk)', "median", "MAD", "IQR", "Q1", "Q3"),
# selected = "sem"),
# actionButton('select_all1','select all'),
# actionButton('deselect_all1','deselect all'),
numericInput("digits", "Digits:", 2, min = 0, max = 5),
hr(),
htmlOutput("legend", width="200px", inline =FALSE),
# ,
# selectInput("stats_hide2", "Select columns to hide", "", multiple = TRUE, choices=list("mean", "sd", "sem","95CI mean", "median", "MAD", "IQR", "Q1", "Q3", "95CI median")
NULL)
),
mainPanel(
tabsetPanel(id="tabs",
tabPanel("Data upload", h4("Data as provided"),
dataTableOutput("data_uploaded")),
tabPanel("Plot", downloadButton("downloadPlotPDF", "Download pdf-file"),
downloadButton("downloadPlotSVG", "Download svg-file"),
# downloadButton("downloadPlotEPS", "Download eps-file"),
downloadButton("downloadPlotPNG", "Download png-file"),
actionButton("settings_copy", icon = icon("clone"),
label = "Clone current setting"),
# actionButton("legend_copy", icon = icon("clone"),
# label = "Copy Legend"),
div(`data-spy`="affix", `data-offset-top`="10", plotOutput("coolplot", height="100%"),
# htmlOutput("LegendText", width="200px", inline =FALSE),
# htmlOutput("HTMLpreset"),
conditionalPanel(condition = "input.show_table == true", h3("Difference with the selected reference")), (tableOutput('toptable')))
),
tabPanel("Data Summary",
h3("Table 1: Statistics for individual replicates"),dataTableOutput('data_summary'),
h3("Table 2: Statistics for conditions"),dataTableOutput('data_summary_condition') ,
h3("Table 3: Statistics for comparison of means between conditions"),dataTableOutput('data_difference'),
h3("Table 4: Statistics for repeatability"),dataTableOutput('data_repeats'),
NULL
),
tabPanel("About", includeHTML("about.html")
)
)
)
)
)
server <- function(input, output, session) {
observe({
showNotification("New feature: conditions can be (de)selected and ordered. Feedback or suggestions to improve the app are appreciated. For contact information, see the 'About' tab. ", duration = 10, type = "warning")
})
fraction_significant <- 0
x_var.selected <- "Treatment"
y_var.selected <- "Speed"
g_var.selected <- "Replicate"
isolate(vals$count <- vals$count + 1)
###### DATA INPUT ###################
df_upload <- reactive({
if (input$data_input == 2) {
data <- df_tidy_example2
x_var.selected <<- "Condition"
y_var.selected <<- "BP"
g_var.selected <<- "N"
} else if (input$data_input == 1) {
data <- df_tidy_example
x_var.selected <<- "Treatment"
y_var.selected <<- "Speed"
g_var.selected <<- "Replicate"
} else if (input$data_input == 3) {
x_var.selected <<- "none"
y_var.selected <<- "none"
g_var.selected <<- "-"
file_in <- input$upload
# Avoid error message while file is not uploaded yet
if (is.null(input$upload)) {
return(data.frame(x = "Click 'Browse...' to select a datafile or drop file onto 'Browse' button"))
# } else if (input$submit_datafile_button == 0) {
# return(data.frame(x = "Press 'submit datafile' button"))
} else {
filename_split <- strsplit(file_in$datapath, '[.]')[[1]]
fileext <- tolower(filename_split[length(filename_split)])
# if (fileext=="xls" || fileext=="xlsx") {
# updateSelectInput(session, 'selectInput', selected = 'Excel')
# }
# isolate({
#### Read Tidy Data #####
if (input$toggle_tidy == FALSE) {
if (fileext=="xls" || fileext=="xlsx") {
data <- readxl::read_excel(file_in$datapath)
} else if (fileext == "txt" || fileext=="csv") {
data <- read.csv(file=file_in$datapath, sep = input$upload_delim, na.strings=c("",".","NA", "NaN", "#N/A"), stringsAsFactors = TRUE)
}
#### Read wide Data and convert #####
} else if (input$toggle_tidy == TRUE) {
if (fileext == "txt" || fileext=="csv") {
df <- read.csv(file=file_in$datapath, sep = input$upload_delim, header = FALSE, stringsAsFactors = FALSE)
} else if (fileext=="xls" || fileext=="xlsx") {
df <- readxl::read_excel(file_in$datapath, col_names = FALSE)
}
labels <- gsub("\\s","", strsplit(input$labels,",")[[1]])
data <- tidy_df(df, n = input$n_conditions, labels = labels)
}
}
} else if (input$data_input == 5) {
x_var.selected <<- "none"
#Read data from a URL
#This requires RCurl
if(input$URL == "") {
return(data.frame(x = "Enter a full HTML address, for example: https://zenodo.org/record/2545922/files/FRET-efficiency_mTq2.csv"))
} else if (url.exists(input$URL) == FALSE) {
return(data.frame(x = paste("Not a valid URL: ",input$URL)))
} else {data <- read.csv(file=input$URL, stringsAsFactors = TRUE)}
#Read the data from textbox
} else if (input$data_input == 4) {
x_var.selected <<- "none"
y_var.selected <<- "none"
g_var.selected <<- "-"
if (input$data_paste == "") {
data <- data.frame(x = "Copy your data into the textbox,
select the appropriate delimiter, and
press 'Submit data'")
} else {
if (input$submit_data_button == 0) {
return(data.frame(x = "Press 'submit data' button"))
} else {
# isolate({
if (input$toggle_tidy == FALSE) {
data <- read_delim(input$data_paste,
delim = input$text_delim,
col_names = TRUE)
} else if (input$toggle_tidy == TRUE) {
df <- read_delim(input$data_paste,
delim = input$text_delim,
col_names = FALSE)
labels <- gsub("\\s","", strsplit(input$labels,",")[[1]])
data <- tidy_df(df, n = input$n_conditions, labels = labels)
}
# })
}
}
}
#Replace space and dot of header names by underscore
data <- data %>%
select_all(~gsub("\\s+|\\.", "_", .))
return(data)
})
##### REMOVE SELECTED COLUMNS #########
df_filtered <- reactive({
if (!is.null(input$use_these_conditions) && input$x_var != "none") {
x_var <- input$x_var
use_these_conditions <- input$use_these_conditions
observe({print(use_these_conditions)})
#Remove the columns that are selected (using filter() with the exclamation mark preceding the condition)
# https://dplyr.tidyverse.org/reference/filter.html
df <- df_upload() %>% filter(.data[[x_var[[1]]]] %in% !!use_these_conditions)
} else {df <- df_upload()}
})
##### CONVERT TO TIDY DATA ##########
##### Get Variables from the input ##############
observe({
var_names <- names(df_upload())
varx_list <- c("none", var_names)
# Get the names of columns that are factors. These can be used for coloring the data with discrete colors
nms_fact <- names(Filter(function(x) is.factor(x) || is.integer(x) ||
is.logical(x) ||
is.character(x),
df_upload()))
nms_var <- names(Filter(function(x) is.integer(x) ||
is.numeric(x) ||
is.double(x),
df_upload()))
vary_list <- c("none",nms_var)
facet_list <- c("-",var_names)
# updateSelectInput(session, "colour_list", choices = nms_fact)
updateSelectInput(session, "y_var", choices = vary_list, selected = y_var.selected)
updateSelectInput(session, "x_var", choices = varx_list, selected = x_var.selected)
updateSelectInput(session, "g_var", choices = facet_list, selected = g_var.selected)
updateSelectInput(session, "h_facet", choices = facet_list)
updateSelectInput(session, "v_facet", choices = facet_list)
# updateSelectInput(session, "filter_column", choices = varx_list, selected="none")
# if (input$add_bar == TRUE) {
# updateSelectInput(session, "alphaInput", min = 0.3)
# }
})
########### When x_var is selected for tidy data, get the list of conditions
observeEvent(input$x_var != 'none' && input$y_var != 'none', {
if (input$x_var != 'none') {
filter_column <- input$x_var
if (filter_column == "") {filter_column <- NULL}
koos <- df_upload() %>% select(for_filtering = !!filter_column)
conditions_list <- levels(factor(koos$for_filtering))
# observe(print((conditions_list)))
updateSelectInput(session, "use_these_conditions", choices = conditions_list)
}
})
###### When a bar is added, make sure that the data is still visible
observeEvent(input$paired, {
if (input$paired==TRUE) {
# update jitter options
updateRadioButtons(session, "jitter_type", choices = list("No offset"="no_jitter", "Distribution only"="violin"))
# update pairing options
updateRadioButtons(session, "connect", choices = list("Dotted line" = "dotted", "Dashed line"= "dashed", "Solid line" ="solid"))
} else if (input$paired==FALSE) {
updateRadioButtons(session, "jitter_type", choices = list("Data & distribution" = "quasirandom", "Jittered data" = "random","No offset"="no_jitter", "Distribution only"="violin"))
# update pairing options
updateRadioButtons(session, "connect", choices = list("No" = "blank", "Dotted line" = "dotted", "Dashed line"= "dashed", "Solid line" ="solid"))
}
})
observeEvent(input$tabs, {
if (input$tabs=='Data Summary') {
df <- df_summ_per_replica()
# Get the list of p-values
p <- (df[,10]) %>% unlist(use.names = F)
# Determine the fraction of p-values that is significant, based on a threshold of 0.05
fraction_significant <<- length(which(p<0.05))/length(p)
if (fraction_significant>0.5 && input$summary_replicate =='mean') {
showNotification("The majority of replicates has a distribution that deviates from normality, as inferred from a p< 0.05 from a Shapiro-wilk test. Consider using the median as a measure of location for the replicates", duration = 10, type = "error")
}
}
})
observeEvent(input$connect, {
if (input$connect!='blank') {
showNotification("Connecting or 'pairing' the data changes the p-value and the 95% confidence interval for the difference", duration = 10, type = "message")
}
})
observeEvent(input$summary_replicate, {
if (input$summary_replicate=="median") {
showNotification("Selecting the median as the measure of location for the replicates does not change the p-value and the difference, as these are calculated from the mean values", duration = 10, type = "message")
}
})
########### GET INPUT VARIABLEs FROM HTML ##############
observe({
query <- parseQueryString(session$clientData$url_search)
############ ?data ################
if (!is.null(query[['data']])) {
presets_data <- query[['data']]
presets_data <- unlist(strsplit(presets_data,";"))
observe(print((presets_data)))
updateRadioButtons(session, "data_input", selected = presets_data[1])
# updateCheckboxInput(session, "tidyInput", value = presets_data[2])
# updateSelectInput(session, "x_var", selected = presets_data[3])
# updateSelectInput(session, "y_var", selected = presets_data[4])
# updateSelectInput(session, "g_var", selected = presets_data[5])
x_var.selected <<- presets_data[3]
y_var.selected <<- presets_data[4]
g_var.selected <<- presets_data[5]
if (presets_data[1] == "1" || presets_data[1] == "2") {
updateTabsetPanel(session, "tabs", selected = "Plot")
}
}
############ ?vis ################
if (!is.null(query[['vis']])) {
presets_vis <- query[['vis']]
presets_vis <- unlist(strsplit(presets_vis,";"))
observe(print((presets_vis)))
#radio, slider, radio, check, slider
updateRadioButtons(session, "jitter_type", selected = presets_vis[1])
updateCheckboxInput(session, "show_distribution", value = presets_vis[2])
updateSliderInput(session, "alphaInput", value = presets_vis[3])
updateRadioButtons(session, "summary_replicate", selected = presets_vis[4])
updateCheckboxInput(session, "connect", value = presets_vis[5])
updateCheckboxInput(session, "show_table", value = presets_vis[6])
updateCheckboxInput(session, "add_shape", value = presets_vis[7])
updateSliderInput(session, "alphaInput_summ", value = presets_vis[8])
updateRadioButtons(session, "ordered", selected = presets_vis[9])
#For backward compatibility with links in the paper
if (length(presets_vis)<10) {dotsize <- 3.5} else {dotsize <- presets_vis[10]}
updateNumericInput(session, "dot_size", value= dotsize)
#select zero
updateRadioButtons(session, "summary_condition", selected = presets_vis[11])
# updateTabsetPanel(session, "tabs", selected = "Plot")
}
############ ?layout ################
if (!is.null(query[['layout']])) {
presets_layout <- query[['layout']]
presets_layout <- unlist(strsplit(presets_layout,";"))
observe(print((presets_layout)))
updateSelectInput(session, "split_direction", selected = presets_layout[1])
updateCheckboxInput(session, "rotate_plot", value = presets_layout[2])
updateCheckboxInput(session, "no_grid", value = (presets_layout[3]))
updateCheckboxInput(session, "change_scale", value = presets_layout[4])
updateCheckboxInput(session, "scale_log_10", value = presets_layout[5])
updateTextInput(session, "range", value= presets_layout[6])
# updateCheckboxInput(session, "color_data", value = presets_layout[6])
updateCheckboxInput(session, "dark", value = presets_layout[7])
updateRadioButtons(session, "adjustcolors", selected = presets_layout[8])
updateCheckboxInput(session, "add_legend", value = presets_layout[9])
if (length(presets_layout)>10) {
updateNumericInput(session, "plot_height", value= presets_layout[10])
updateNumericInput(session, "plot_width", value= presets_layout[11])
}
# updateTabsetPanel(session, "tabs", selected = "Plot")
}
############ ?color ################
if (!is.null(query[['color']])) {
presets_color <- query[['color']]
observe(print((presets_color)))
presets_color <- unlist(strsplit(presets_color,";"))
color_list <- gsub("_", "#", presets_color[2])
observe(print((color_list)))
# updateSelectInput(session, "colour_list", selected = presets_color[1])
updateTextInput(session, "user_color_list", value= color_list)
}
############ ?label ################
if (!is.null(query[['label']])) {
presets_label <- query[['label']]
presets_label <- unlist(strsplit(presets_label,";"))
observe(print((presets_label)))
updateCheckboxInput(session, "add_title", value = presets_label[1])
updateTextInput(session, "title", value= presets_label[2])
updateCheckboxInput(session, "label_axes", value = presets_label[3])
updateTextInput(session, "lab_x", value= presets_label[4])
updateTextInput(session, "lab_y", value= presets_label[5])
updateCheckboxInput(session, "adj_fnt_sz", value = presets_label[6])
updateNumericInput(session, "fnt_sz_ttl", value= presets_label[7])
updateNumericInput(session, "fnt_sz_labs", value= presets_label[8])
updateNumericInput(session, "fnt_sz_ax", value= presets_label[9])
# updateNumericInput(session, "fnt_sz_cand", value= presets_label[10])
updateCheckboxInput(session, "add_legend", value = presets_label[11])
}
############ ?url ################
if (!is.null(query[['url']])) {
updateRadioButtons(session, "data_input", selected = 5)
updateTextInput(session, "URL", value= query[['url']])
observe(print((query[['url']])))
updateTabsetPanel(session, "tabs", selected = "Plot")
}
})
########### RENDER URL ##############
output$HTMLpreset <- renderText({
url()
})
######### GENERATE URL with the settings #########
url <- reactive({
base_URL <- paste(sep = "", session$clientData$url_protocol, "//",session$clientData$url_hostname, ":",session$clientData$url_port, session$clientData$url_pathname)
# data <- c(input$data_input, "", input$x_var, input$y_var, input$h_facet, input$v_facet)
data <- c(input$data_input, "", input$x_var, input$y_var, input$g_var)
vis <- c(input$jitter_type, input$show_distribution, input$alphaInput, input$summary_replicate, input$connect, input$show_table, input$add_shape, input$alphaInput_summ, input$ordered, input$dot_size, input$summary_condition)
layout <- c(input$split_direction, input$rotate_plot, input$no_grid, input$change_scale, input$scale_log_10, input$range, input$dark,
input$adjustcolors, input$add_legend, input$plot_height, input$plot_width)
#Hide the standard list of colors if it is'nt used
if (input$adjustcolors != "5") {
color <- c("x", "none")
} else if (input$adjustcolors == "5") {
stripped <- gsub("#", "_", input$user_color_list)
color <- c("X", stripped)
}
# label <- c(input$add_title, input$title, input$label_axes, input$lab_x, input$lab_y, input$adj_fnt_sz, input$fnt_sz_ttl, input$fnt_sz_ax, input$add_legend)
label <- c(input$add_title, input$title, input$label_axes, input$lab_x, input$lab_y, input$adj_fnt_sz, input$fnt_sz_title, input$fnt_sz_labs, input$fnt_sz_ax, "", input$add_legend)
#replace FALSE by "" and convert to string with ; as seperator
data <- sub("FALSE", "", data)
data <- paste(data, collapse=";")
data <- paste0("data=", data)
vis <- sub("FALSE", "", vis)
vis <- paste(vis, collapse=";")
vis <- paste0("vis=", vis)
layout <- sub("FALSE", "", layout)
layout <- paste(layout, collapse=";")
layout <- paste0("layout=", layout)
color <- sub("FALSE", "", color)
color <- paste(color, collapse=";")
color <- paste0("color=", color)
label <- sub("FALSE", "", label)
label <- paste(label, collapse=";")
label <- paste0("label=", label)
if (input$data_input == "5") {url <- paste("url=",input$URL,sep="")} else {url <- NULL}
parameters <- paste(data, vis,layout,color,label,url, sep="&")
preset_URL <- paste(base_URL, parameters, sep="?")
observe(print(parameters))
observe(print(preset_URL))
return(preset_URL)
})
############# Pop-up that displays the URL to 'clone' the current settings ################
observeEvent(input$settings_copy , {
showModal(urlModal(url=url(), title = "Use the URL to launch SuperPlotsOfData with the current setting"))
})
observeEvent(input$legend_copy , {
showModal(urlModal(url=Fig_legend(), title = "Legend text"))
})
######## ORDER the Conditions #######
df_sorted <- reactive({
klaas <- df_selected()
if(input$ordered == "median") {
klaas$Condition <- reorder(klaas$Condition, klaas$Value, median, na.rm = TRUE)
} else if (input$ordered == "none") {
if (!is.null(input$use_these_conditions)) {
# Set order based on input
klaas$Condition <- factor(klaas$Condition, levels = input$use_these_conditions)}
else {
klaas$Condition <- factor(klaas$Condition, levels=unique(klaas$Condition))
}
} else if (input$ordered == "alphabet") {
klaas$Condition <- factor(klaas$Condition, levels=unique(sort(klaas$Condition)))
}
return(klaas)
})
######## Extract the data for display & summary stats #######
df_selected <- reactive({
df_temp <- df_filtered()
x_choice <- input$x_var
y_choice <- input$y_var
g_choice <- input$g_var
#Prevent error if y parameter is not selected
if (input$y_var =='none') {
koos <- df_temp %>% dplyr::select(Condition = !!x_choice)
koos$Value <- 1
koos$Replica <- as.factor("1")
return(koos)
}
if (g_choice == "-") {
if (input$x_var =='none') {
koos <- df_temp %>% dplyr::select(Value = !!y_choice) %>% filter(!is.na(Value))
koos$Replica <- as.factor("1")
koos$Condition <- as.factor("1")
} else {
koos <- df_temp %>% dplyr::select(Condition = !!x_choice , Value = !!y_choice) %>% filter(!is.na(Value))
koos$Replica <- as.factor("1")
}
} else {