Commit f1ed4b89 authored by GAREL Marc's avatar GAREL Marc
Browse files

add smooth parameter explaiantation

parent 13ced342
##################################################
## Project: Shiny app allowing plot and parameters for microbial growth dataset
## Script purpose: Perform logistic regression to estimate growth rate and maximum cells density
## Initial Date: October 2017
## Last Update : February 2019
## Version : 2.0
## Author: Marc Garel, Severine Martini, Lloyd Izard, Christian Tamburini
##################################################
### libraries
library(shiny)
library(DT)
library(rgl)
library(quantreg)
library(SparseM)
library(rmarkdown)
### ui script
shinyUI(
fluidPage(
navbarPage("Application of a logistic model on microbial datasets",
tabPanel("Upload data",
sidebarLayout(
sidebarPanel("",
fileInput('file1', 'Upload your dataset (.csv or .txt)',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv', '.txt')),
# download demo file
downloadButton("downloadDataDemo", label = "Download a demo dataset"),
# header or not header
checkboxInput('header', 'Header', TRUE),
#
radioButtons('sep', 'Dataset separator',
c(Comma=',', Semicolon=';', Tab='\t'), selected="\t"),
#
radioButtons('dec', 'Decimal separator',
c(Point='.', Comma=','), selected=".")
),
mainPanel(
helpText('This app aims at estimating the growth rate and maximum cells density using non-linear regression.
The method is detailled in Martini et al. (2013).',
br(),
br(),
'A demo dataset is available in "Download a demo dataset", you can save it in your computer and load it using "Browse", or you can also browse your own dataset.',
br(),
br(),
'In order to run this application, you have to format your dataset with tabulation separators. Also, remove all spaces in the dataset header (prefer to use "_" when needed).
Organise your dataset so that there is only two arrays. The first one being the time and the second one, the cells density
(e. g. optic density, cell number, biomass). This application proposes a method to perform ', strong('a logistic regression'), ' to estimate', strong('growth rate'), 'as well as ', strong('maximum cells density'),'.'),
withMathJax(helpText('The logistic equation is defined as $$x(t) = r.x_0.(1-\\frac{x_0}K)$$'))
)
)
),
tabPanel("Uploaded data",
DT::dataTableOutput("raw_data")
),
tabPanel("Plot",
sidebarLayout(
sidebarPanel("",
textInput("xlabel", "xlabel", value = "Time (h)"),
textInput("ylabel", "ylabel", value = "Biomass"),
textInput("xmin", "xmin", value = 0),
textInput("xmax", "xmax", value = 100),
textInput("ymin", "ymin", value = 0),
textInput("ymax", "ymax", value = 100),
numericInput("test", "Smooth value ranged between 0 and 1 ", value = 1, min=0, max=1,step=0.01),
downloadButton("downloadDataParameters", "Download parameters"),
downloadButton("downloadDataCalculated", "Download plot data")
),
mainPanel(
plotOutput("raw_plot"),
DT::dataTableOutput("data"),
DT::dataTableOutput("parameters")
)
)
),
navbarMenu("Verify parameters estimation",
tabPanel("2D",
plotOutput("verify_plot_2D")),
tabPanel("3D",
rglwidgetOutput("verify_plot_3D", width = 800, height = 800))),
tabPanel("Citation",
verbatimTextOutput("citation")),
tabPanel("About",
helpText('This App, developed in 2020, is based on a teamwork between researchers and students.
The PIs are Marc Garel (Mediterranean Institute of Oceanography/Aix-Marseille University/OSU Pytheas/CNRS) and Séverine Martini (Mediterranean Institute of Oceanography/Aix-Marseille University/OSU Pytheas/CNRS), Marthe Vienne (Bsc student) improved the app with statistical tools and Lloyd Izard (MSc Student) has been involved into the developpement of the app.'))
)
)
)
##################################################
## Project: Shiny app allowing plot and parameters for microbial growth dataset
## Script purpose: Perform logistic regression to estimate growth rate and maximum cells density
## Initial Date: October 2017
## Last Update : February 2019
## Version : 2.0
## Author: Marc Garel, Severine Martini, Lloyd Izard, Christian Tamburini
##################################################
### libraries
library(shiny)
library(DT)
library(rgl)
library(quantreg)
library(SparseM)
library(rmarkdown)
### ui script
shinyUI(
fluidPage(
navbarPage("Application of a logistic model on microbial datasets",
tabPanel("Upload data",
sidebarLayout(
sidebarPanel("",
fileInput('file1', 'Upload your dataset (.csv or .txt)',
accept=c('text/csv', 'text/comma-separated-values,text/plain', '.csv', '.txt')),
# download demo file
downloadButton("downloadDataDemo", label = "Download a demo dataset"),
# header or not header
checkboxInput('header', 'Header', TRUE),
#
radioButtons('sep', 'Dataset separator',
c(Comma=',', Semicolon=';', Tab='\t'), selected="\t"),
#
radioButtons('dec', 'Decimal separator',
c(Point='.', Comma=','), selected=".")
),
mainPanel(
helpText('This app aims at estimating the growth rate and maximum cells density using non-linear regression.
The method is detailled in Martini et al. (2013).',
br(),
br(),
'A demo dataset is available in "Download a demo dataset", you can save it in your computer and load it using "Browse", or you can also browse your own dataset.',
br(),
br(),
'On Plot panel, it is possible to set axes labels, axes range and Smooth. Smooth parameter can compute theorical (downloadable) for to use with other activities.',
br(),
br(),
'In order to run this application, you have to format your dataset with tabulation separators. Also, remove all spaces in the dataset header (prefer to use "_" when needed).
Organise your dataset so that there is only two arrays. The first one being the time and the second one, the cells density
(e. g. optic density, cell number, biomass). This application proposes a method to perform ', strong('a logistic regression'), ' to estimate', strong('growth rate'), 'as well as ', strong('maximum cells density'),'.'),
withMathJax(helpText('The logistic equation is defined as $$x(t) = r.x_0.(1-\\frac{x_0}K)$$'))
)
)
),
tabPanel("Uploaded data",
DT::dataTableOutput("raw_data")
),
tabPanel("Plot",
sidebarLayout(
sidebarPanel("",
textInput("xlabel", "xlabel", value = "Time (h)"),
textInput("ylabel", "ylabel", value = "Biomass"),
textInput("xmin", "xmin", value = 0),
textInput("xmax", "xmax", value = 100),
textInput("ymin", "ymin", value = 0),
textInput("ymax", "ymax", value = 100),
numericInput("test", "Smooth value ranged between 0 and 1 ", value = 1, min=0, max=1,step=0.01),
downloadButton("downloadDataParameters", "Download parameters"),
downloadButton("downloadDataCalculated", "Download plot data")
),
mainPanel(
plotOutput("raw_plot"),
DT::dataTableOutput("data"),
DT::dataTableOutput("parameters")
)
)
),
navbarMenu("Verify parameters estimation",
tabPanel("2D",
plotOutput("verify_plot_2D")),
tabPanel("3D",
rglwidgetOutput("verify_plot_3D", width = 800, height = 800))),
tabPanel("Citation",
verbatimTextOutput("citation")),
tabPanel("About",
helpText('This App, developed in 2020, is based on a teamwork between researchers and students.
The PIs are Marc Garel (Mediterranean Institute of Oceanography/Aix-Marseille University/OSU Pytheas/CNRS) and Séverine Martini (Mediterranean Institute of Oceanography/Aix-Marseille University/OSU Pytheas/CNRS), Marthe Vienne (Bsc student) improved the app with statistical tools and Lloyd Izard (MSc Student) has been involved into the developpement of the app.'))
)
)
)
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