Commit d3f3f4bc authored by Bagueneau Mathias's avatar Bagueneau Mathias
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- ReadMe

- Bug fix (messages demandant une upload de fichier)
parent c9aa85a3
# ~ Shiny SChnurR
![](https://zupimages.net/up/19/17/rcn0.png)
*Jean-Baptiste Alberge, Jonathan Cruard, Mathias Bagueneau*
![](https://zupimages.net/up/19/18/zpld.png)
</br>
**Direct Link of the Tool :** https://shiny-bird.univ-nantes.fr/jbalberge/schnurr/
# - Introduction
Shiny SChnurR is a visualisation tool for single-cell RNA-seq analysis developped in R Shiny.
# - Installation
To use Shiny SChnurR, you first need to :
1. Install [R][R], version 3.5 or greater
2. Install some packages (*cf Required Packages part* ), like **Shiny**
3. Download all the files of this project
1. Install [R][R], version 3.5 or greater.
2. Install some packages (*cf Required Packages part* ).
3. Download all files of this project, or clone it.
Then, you simply need to launch R and this command :
......@@ -24,15 +23,16 @@ Then, you simply need to launch R and this command :
shiny::runApp('/my/path/to/my/folder/which/contain/all/the/files')
```
The *rds files used must have been made with the pipeline available at this adress :
The .rds files used must have been made with the analysis pipeline available at this adress :
https://gitlab.univ-nantes.fr/E176261N/singlecell
## Required Packages
Here the list of the required packages for Shiny SChnurR :
* [shiny][shiny]
* [Shiny][Shiny]
* [Seurat][Seurat] : **The version 3 is required !**
* [sctransform][sctransform]
* [SCTransform][Sctransform]
* shinythemes
* dplyr
* ggplot2
......@@ -49,32 +49,80 @@ Here the list of the required packages for Shiny SChnurR :
* data.table
* clusterProfiler
* org.Hs.eg.db
* tools
An installer is planned...
# - Tutorial
Shiny SChnurR is a visualisation tool. Many options are available into the different pages.
Many options are available into the different pages.
## Visualisation Page
Redaction in progress...
Once you launch the app, the first page is the Visualisation page.
You first need to upload a .rds file, or choose one already provided as example.
Then, many information are provided :
* Some files information, with genes and cells number, and the assay used.
* Two graphs for the visualisation.
* A data table with some pre-calculated markers.
The first graph allows you to visualise by all the factors (resolution, idents, ...) of your file.
The second one is for the features or data (all the genes repartitions, scores, ...).
The two graphs could be controlled with the panel made for. You have two graph modes : t-SNE or UMAP, and clusters informations for every factors.
On the graphs, you could also select some cells, and have the percentage of your selection by the total cell number.
The data table under the graphs is pre-calculated depending the selected factor.
It shows all significant markers, calculated with the test MAST. You could affine your marker research with the filters.
All of the outputs are exportable : in .svg for the graphs and in .csv for the table.
## HeatMap Page
Redaction in progress...
The HeatMap page allows you to do a HeatMap with many parameters.
You could choose a factor and the number of top genes you want to be shown.
The HeatMap also use the pre-calculated markers for each factors (like the data table from the visualisation page).
The HeatMap is exportable in .svg.
## Genes Page
Redaction in progress...
Page in progress...
## Compare Page
Redaction in progress...
In this page, you could compare groups from factors with each other.
You could choose multiple groups, and also add a second factor to filter with.
Then you could Find the significant markers of your selection.
Be carefull to not select redondant cells.
Like the Visualisation page, you have a Control panel to change some parameters to the graphs (like graph mode, point size, ...) and choose what you want to see (factors, features, ...).
All of the outputs are exportable : in .svg for the graphs and in .csv for the table.
## Pipeline Page
Redaction in progress...
This page presents the different tools used in the analysis pipeline.
_____________________________
### About
**- Shiny SChnurR -**
Centre de Recherche en Cancérologie et Immunologie Nantes-Angers
UMR1232, CNRS ERL6001
IRS-UN - 8 Quai Moncousu - 44007 Nantes
**Equipe 11** 'Oncogénomique intégrative de la genèse et de la progression du Myélome Multiple'
*Jean-Baptiste Alberge, Jonathan Cruard, Mathias Bagueneau*
----
......
......@@ -218,8 +218,8 @@ body <- dashboardBody(
p("8 Quai Moncousu"),
p("44007 Nantes"), br(),
img(src = "crcina.png", height = 180, width = 400),
br(), br(), p(em("Development Team : Jean-Baptiste ALBERGE, Jonathan CRUARD, Mathias BAGUENEAU")),
br(), p(em("Beta-test : Benjamin DELAUNE")), br(), p(strong("Git repository :"),a(href="https://gitlab.univ-nantes.fr/MathBgn/myelome", "Shiny SChnurR"))
br(), br(), p(em("Development Team : Jean-Baptiste ALBERGE, Jonathan CRUARD, Mathias BAGUENEAU"), br(), em("Beta-test : Benjamin DELAUNE")),
br(), p(strong("Git repository :"),a(href="https://gitlab.univ-nantes.fr/MathBgn/myelome", "Shiny SChnurR"), br(), em("A complete tutorial is findable in this."))
)
)
)
......@@ -381,7 +381,7 @@ server <- function(input, output, session) {
output$markers_table <- renderDataTable ({
req(wrfile())
req(markersData() != "")
datatable(markersData()[c(6,3,4,2,1,5)], filter="top", caption = paste("Table 1 : All significant markers for the factor :", input$fsel ,"| Test used : MAST" )) %>% formatRound(columns=c(2,3,4), digits=5) %>% formatSignif(columns=c(6,5), digits=5)
datatable(markersData()[c(6,3,4,2,1,5)], filter="top", caption = paste("Table 1 : All significant markers for the factor :", input$fsel ,"| Test used : MAST" )) %>% formatRound(columns=c(2,3,4), digits=3) %>% formatSignif(columns=c(6,5), digits=3)
})
output$miniplot_compare <- renderPlot({
......@@ -561,15 +561,18 @@ server <- function(input, output, session) {
## No file texts --------
output$no_file2 <- renderText({
req(is.null(wrfile()))
req(input$file =="")
req(is.null(input$file1))
print("Please upload or \n choose a file")
})
output$no_file3 <- renderText({
req(is.null(wrfile()))
req(input$file =="")
req(is.null(input$file1))
print("Please upload or \n choose a file")
})
output$no_file4 <- renderText({
req(is.null(wrfile()))
req(input$file =="")
req(is.null(input$file1))
print("Please upload or \n choose a file")
})
......@@ -771,7 +774,7 @@ server <- function(input, output, session) {
# In the 2 cases :
output$markers_compare <- renderDataTable ({
req(wrfile())
withProgress(datatable(df[c(1,4,5,3,2,6)], rownames=FALSE, filter="top", caption = "Table 2 : Significant markers of your query | Test used : MAST" ), message = "Render DataTable", value=1) %>% formatRound(columns=c(1,2,3,4), digits=5) %>% formatSignif(columns=c(6,5), digits=5)
withProgress(datatable(df[c(1,4,5,3,2,6)], rownames=FALSE, filter="top", caption = "Table 2 : Significant markers of your query | Test used : MAST" ), message = "Render DataTable", value=1) %>% formatRound(columns=c(1,2,3,4), digits=3) %>% formatSignif(columns=c(6,5), digits=3)
})
output$dlmarkbutton_compare <- renderUI ({
downloadButton("dlmarkers_compare", label="")
......
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