Commit 783803a7 authored by Bagueneau Mathias's avatar Bagueneau Mathias
Browse files

- Update du ReadMe

- Update du .gitignore
- Ajout des jeux de donénes 8kpbmc et AML-027 (sur le serveur également)
- Ontologie de l'onglet Compare fonctionnelle !
parent cebca65c
......@@ -5,5 +5,6 @@
*.Rproj
~/data/
*.rds
!8kpbmc_red.rds
!8kpbmc.rds
!AML-027.rds
......@@ -59,16 +59,16 @@ All of this packages are installed with the provided script **install.R** and ar
Many options are available into the different pages.
## Visualisation Page
## Visualization Page
Once you launch the app, the first page is the Visualisation page.
Once you launch the app, the first page is the Visualization 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.
* Two graphs for the visualization.
* A data table with some pre-calculated markers.
......@@ -87,7 +87,7 @@ All of the outputs are exportable : in .svg for the graphs and in .csv for the t
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 also use the pre-calculated markers for each factors (like the data table from the visualization page).
The HeatMap is exportable in .png.
......@@ -100,7 +100,7 @@ Then you will have a graph (you can also change the graph mode), and two tables.
The first table gives you the list of the genes present in your selection.
The second one gives you the ontology.
The Gene Ontology also use the pre-calculated markers for each factors (like the data table from the visualisation page and the HeatMap).
The Gene Ontology also use the pre-calculated markers for each factors (like the data table from the visualization page and the HeatMap).
All of the outputs are exportable : in .png for the graph and in .csv for the tables.
......@@ -109,12 +109,18 @@ All of the outputs are exportable : in .png for the graph and in .csv for the ta
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, or also do a Gene Ontology like in the Genes page (but here, the markers are calculated before the ontology).
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, ...).
After this, another option and two text areas appears. The text areas are filled with the top 30 genes upregulated from one condition against the other. These areas are writable (you can add or remove some genes).
Then you could do a gene ontology with these two lists.
The results are into two tables.
All of the outputs are exportable : in .svg for the graphs and in .csv for the table.
Like the Visualization 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, ...).
You could also choose an ontology.
All of the outputs are exportable : in .svg for the graphs and in .csv for the tables.
You could also export the barcodes of the selected cells, in .csv.
## Pipeline Page
......
This diff is collapsed.
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment