Commit 443ea37e authored by Stevenn Volant's avatar Stevenn Volant
Browse files

ajout modif amine

parent 60e00139
......@@ -374,7 +374,7 @@ CheckCountsTable <- function(counts)
if(type!="hori")
{
par(cex=input$cexTitleDiag,mar = c(0.3,2,0.3,2))
res = circlize_dendrogram(dend, labels_track_height = NULL, dend_track_height = .3, main = "Cluster dendrogram",xlab = paste(input$DistClust,"distance, Ward criterion",sep=" "))
res = circlize_dendrogram(dend, labels_track_height = 0.2, dend_track_height = .3, main = "Cluster dendrogram",xlab = paste(input$DistClust,"distance, Ward criterion",sep=" "))
}
return(res)
}
......@@ -742,7 +742,7 @@ CheckCountsTable <- function(counts)
ord = abs(ord[2] - ord[1])/25
par(mfrow = c(1, 2),cex=input$cexTitleDiag,mar=c(6,6,4,5))
plot(pca$x[, 1], pca$x[, 2], las = 1, cex = cex=input$cexTitleDiag, col = col[as.integer(group[,1])],
plot(pca$x[, 1], pca$x[, 2], las = 1, cex = input$cexTitleDiag, col = col[as.integer(group[,1])],
pch = if (ncol1) {16}
else {c(16:18, 25)[as.integer(group[, 2])]},
xlab = paste0("PC1 (", prp[1], "%)"),
......@@ -755,7 +755,7 @@ CheckCountsTable <- function(counts)
abs = abs(abs[2] - abs[1])/25
ord = range(pca$x[, 3])
ord = abs(ord[2] - ord[1])/25
plot(pca$x[, 1], pca$x[, 3], las = 1, cex = cex=input$cexTitleDiag, col = col[as.integer(group[, 1])],
plot(pca$x[, 1], pca$x[, 3], las = 1, cex = input$cexTitleDiag, col = col[as.integer(group[, 1])],
pch = if (ncol1) {16}
else {c(16:18, 25)[as.integer(group[, 2])]},
xlab = paste0("PC1 (", prp[1], "%)"),
......
if (!require("Rcpp")){
install.packages("Rcpp")
}
if(!require(shinydashboard)){
install.packages('shinydashboard')
library(shinydashboard)
}
if(!require(rjson)){
install.packages('rjson')
}
if(!require(devtools)){
install.packages('devtools')
}
<<<<<<< HEAD
=======
#library(plotly)
>>>>>>> 84440282f7e33f02d6a643f231ab33bf935f89c1
if (!require(psych)) {
install.packages('psych')
library(psych)
}
if (!require(ggplot2)) {
install.packages('ggplot2')
library(ggplot2)
}
if (!require(vegan)) {
install.packages('vegan')
library(vegan)
}
if (!require(dendextend)) {
install.packages('dendextend')
library(dendextend)
}
if (!require(circlize)) {
install.packages('circlize')
library(circlize)
}
if (!require(d3heatmap)) {
install.packages('d3heatmap')
library(d3heatmap)
}
if (!require(biom)) {
install.packages('biom')
library(biom)
}
if (!require(devtools)) {
install.packages('devtools')
}
if (!require(rNVD3)) {
library(devtools)
install_github('rNVD3', 'ramnathv')
}
source("internal.R")
renderDataTable <- DT::renderDataTable
......@@ -926,7 +971,7 @@ shinyServer(function(input, output,session) {
resDiff = ResDiffAnal()
Plot_diag_Eigen(input,resDiff)
},height = 400)
},height =400)
SizeFactor_table <-reactive({
res = ResDiffAnal()
......
library(shinydashboard)
# if (!require(rNVD3)) {
# install.packages('rNVD3')
# library(rNVD3)
# }
if(!require(shinydashboard)){
install.packages('shinydashboard')
library(shinydashboard)
}
if (!require(psych)) {
install.packages('psych')
library(psych)
}
if (!require(ggplot2)) {
install.packages('ggplot2')
library(ggplot2)
}
if (!require(vegan)) {
install.packages('vegan')
library(vegan)
}
if (!require(dendextend)) {
install.packages('dendextend')
library(dendextend)
}
if (!require(circlize)) {
install.packages('circlize')
library(circlize)
}
if (!require(biom)) {
install.packages('biom')
library(biom)
}
if (!require(DT)) {
install.packages('DT')
library(DT)
}
if (!require(RColorBrewer)) {
install.packages('RColorBrewer')
library(RColorBrewer)
}
if (!require(gplots)) {
install.packages('gplots')
library(gplots)
}
if (!require(DESeq2)) {
source("https://bioconductor.org/biocLite.R")
biocLite("DESeq2")
library(DESeq2)
}
if (!require(ade4)) {
install.packages('ade4')
library(ade4)
}
}
sidebar <- dashboardSidebar(
sidebarMenu(
menuItem("Home", tabName = "Home", icon = icon("home")),
menuItem("Tutorial", tabName = "Tutorial", icon = icon("book")),
menuItem("Upload your data", tabName = "Upload", icon = icon("upload")),
menuItemOutput("dymMenu")
)
)
body <- dashboardBody(
tabItems(
tabItem(tabName = "Home",
tabBox(title="Welcome to Meta16S", id="tabset1", height = "900px", width = 12,
tabPanel("About", p("Meta16S is a web interface for the analysis of metagenomic data including the normalization,
the differential analysis and mutiple visualization.",style = "font-family: 'times'; font-si16pt"),
p("Meta16S is based on DESeq2 R package", a("[Anders and Huber 2010]", href="http://www.ncbi.nlm.nih.gov/pubmed/20979621"), "for the analysis of metagenomic data, as suggested in", a("[McMurdie and Holmes 2014]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/"),
". Meta16S robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2", a("[Love 2014]", href="http://www.ncbi.nlm.nih.gov/pubmed/25516281"),".
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1.fr/ade4/"), "and plots are generated with", a("ggplot2",href="http://ggplot2.org/"), "or", a("D3.js packages",href="http://d3js.org/"), ".", style = "font-family: 'times'; font-si16pt")),
tabPanel("Authors", h3("The main contributors to Meta16s:"),
p(a("Stevenn Volant", href="mailto:stevenn.volant"), "(Initiator, coding, testing, documentation, evaluation)"),
p(a("Amine Ghozlane",href="mailto:amine.ghozlane@pasteur.fr"), "(Coding, testing, documentation, feature suggestions)"),
p(a("Pierre Lechat",href="mailto:pierre.lechat@pasteur.fr"), "(Coding, testing, feature suggestions)"),
p(a("Marie-Agnès Dillies",href="mailto:marie-agnes.dillies@pasteur.fr"), "(Evaluation)"),
h3("Acknowledgements"),
p("Thanks to the following people for patches and other suggestions for improvements:"),
p(a("Christophe Malabat",href="mailto:christophe.malabat@pasteur.fr"))),
tabPanel("Citing Meta16S",p("No papers about Meta16s have been published yet, but a manuscript is in preparation."),
p("For now, if you have any comments, questions or suggestions, or want to use meta16s please contact", a("Dr. Marie-Agnès Dillies", href="mailto:marie-agnes.dillies@pasteur.fr"),".", style = "font-family: 'times'; font-si16pt; color:red")))),
tabBox(title="Welcome to Meta16S", id="tabset1", height = "700", width = 12,
tabPanel("About", p("Meta16S is a web interface for the analysis of metagenomic data including the normalization,
the differential analysis and mutiple visualization.",style = "font-family: 'times'; font-si16pt"),
p("Meta16S is based on DESeq2 R package", a("[Anders and Huber 2010]", href="http://www.ncbi.nlm.nih.gov/pubmed/20979621"), "for the analysis of metagenomic data, as suggested in", a("[McMurdie and Holmes 2014]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/"),
". Meta16S robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2", a("[Love 2014]", href="http://www.ncbi.nlm.nih.gov/pubmed/25516281"),".
Resulting p-values are adjusted according to the Benjamini and Hochberg procedure [Benjamini and Hochberg 1995].
The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1.fr/ade4/"), "and plots are generated with", a("ggplot2",href="http://ggplot2.org/"), "or", a("D3.js packages",href="http://d3js.org/"), ".", style = "font-family: 'times'; font-si16pt")),
tabPanel("Authors", h3("The main contributors to Meta16s:"),
p(a("Stevenn Volant", href="mailto:stevenn.volant@pasteur.fr"), "(Initiator, coding, testing, documentation, evaluation)"),
p(a("Amine Ghozlane",href="mailto:amine.ghozlane@pasteur.fr"), "(Coding, testing, documentation, evaluation)"),
p(a("Hugo Varet",href="mailto:hugo.varet@pasteur.fr"), "(Coding, testing, feature suggestions)"),
p(a("Pierre Lechat",href="mailto:pierre.lechat@pasteur.fr"), "(Coding, testing, feature suggestions)"),
p(a("Marie-Agnès Dillies",href="mailto:marie-agnes.dillies@pasteur.fr"), "(Evaluation)"),
p(a("Sean Kennedy",href="mailto:sean.kennedy@pasteur.fr"), "(Evaluation)"),
h3("Acknowledgements"),
p("Thanks to the following people for patches and other suggestions for improvements:"),
p(a("Christophe Malabat",href="mailto:christophe.malabat@pasteur.fr"))),
tabPanel("Citing Meta16S",p("No papers about Meta16s have been published yet, but a manuscript is in preparation.",style = "font-family: 'times'; font-si16pt"),
p("For now, if you have any comments, questions or suggestions, or want to use meta16s please contact", a("Dr. Marie-Agnès Dillies", href="mailto:marie-agnes.dillies@pasteur.fr"),".", style = "font-family: 'times'; font-si16pt; color:red"))
),
img(src = "logo.jpg", height = 90, width = 600,align="right")
),
tabItem(tabName = "Tutorial",
h2("How to !")
),
tabItem(tabName = "Upload",
tags$style(type='text/css', ".well { max-width: 20em; }"),
fluidRow(
......@@ -200,9 +281,9 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
tabItem(tabName = "DiagPlotTab",
fluidRow(
column(width=9,
box(title = "Plot", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotDiag")
),
plotOutput("PlotDiag",height="100%"),
br(),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
box(title = "Size factors", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
dataTableOutput("SizeFactTable")
......@@ -211,12 +292,12 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotEigen")
plotOutput("PlotEigen",height="100%")
)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotpcoaEigen")
plotOutput("PlotpcoaEigen",height="100%")
)
)
......@@ -233,11 +314,14 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
conditionalPanel(condition="input.DiagPlot!='Sfactors' && input.DiagPlot!='SfactorsVStot' ",uiOutput("VarIntDiag")),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'",
h5(strong("Select the modalities")),
uiOutput("ModMat"),
selectInput("DistPCOA","Distance",c("euclidean", "canberra", "bray", "kulczynski", "jaccard",
"gower", "altGower", "morisita", "horn","mountford","raup","binomial",
"chao","cao","mahalanobis"),selected="jaccard")
uiOutput("ModMat")
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='SERE' || input.DiagPlot=='clustPlot' ",
selectInput("DistClust","Distance",c("euclidean", "SERE"="sere", "canberra", "bray", "kulczynski", "jaccard",
"gower", "altGower", "morisita", "horn","mountford","raup","binomial",
"chao","cao","mahalanobis"),selected="jaccard")
)
# conditionalPanel(condition="input.RadioPlotBi=='Nuage'",selectInput("ColorBiplot", "Couleur",choices=c("Bleue" = 'blue',"Rouge"='red',"Vert"='green', "Noir"='black'),width="50%")),
# sliderInput("TransAlphaBi", "Transparence",min=1, max=100, value=50, step=1),
# conditionalPanel(condition="input.RadioPlotBi!='Nuage'", radioButtons("SensGraphBi","Sens du graph",choices=c("Vertical"="Vert","Horizontal"="Hori"))),
......@@ -249,6 +333,8 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
# h6(strong("Layout")),
# numericInput("NbcolSfactors", h6("Columns"),min=1,value = NA)
# ),
sliderInput("heightDiag", "Height",min=100,max=1500,value = 500,step =10),
conditionalPanel(condition="input.DiagPlot=='clustPlot'",
h6(strong("Layout")),
selectInput("typeHculst", h6("Type"),c("Horizontal"="hori","Fan"="fan")),
......@@ -261,8 +347,17 @@ The PCOA is performed with the", a("ade4 R package",href="http://pbil.univ-lyon1
sliderInput("cexstar", "Star height",min=0,max=1,value = 0.95,step =0.1)
),
sliderInput("cexLabelDiag", "Label size",min=0,max=5,value = 1,step =0.1)
# sliderInput("heightDiag", "height",min=100,max=1500,value = 500,step =10),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
checkboxInput("addLabelSFact","Add label",FALSE)
),
fluidRow(
column(width=12, p(strong("Size"))),
column(width=6,sliderInput("cexTitleDiag", h6("Axis"),min=0,max=5,value = 1,step =0.1)),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot' || input.DiagPlot=='pcaPlot'",column(width=6,sliderInput("cexLabelDiag", h6("Points"),min=0,max=5,value = 1,step =0.1)))
)
# sliderInput("widthDiag", "width",min=100,max=1500,value = 1000,step =10)
......
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