diff --git a/README.md b/README.md
index 4e4f944e22a5d80dd9be8b6642cd0c7948bf1a88..13b62853f9ab17ef3506ad7cd33295bb36de4f97 100644
--- a/README.md
+++ b/README.md
@@ -4,45 +4,4 @@ JASS is a python package that handles the computation of the joint statistics ov
 
 ## Documentation
 
-Detailed documentation, describing the setup, usage, and the architecture is available at http://statistical-genetics.pages.pasteur.fr/jass/
-
-## install
-
-You need **python3** to install and use JASS.
-
-```
-# install
-pip install git+https://gitlab.pasteur.fr/statistical-genetics/jass
-```
-
-## configure and import data
-
-```
-# configure
-export JASS_DATA_DIR=/tmp/JASSDATA
-# import GWAS data into JASS
-python -m jass create_init_table [TODO use IMpG format]
-```
-
-## run a server
-
-```
-# launch celery to process tasks
-celery -A jass worker
-# launch the web server
-python -m jass serve
-```
-
-## use JASS on the command line
-
-```
-# list available phenotypes on the command line
-python -m jass list-phenotypes
-# compute joint statistics on the command line into an HDF file
-python -m jass create-worktable --phenotypes z_RA_RA z_ReproGen_AME --worktable-path testwt.h5
-# create the global manhattan plot for a joint statistics file
-python -m jass plot-manhattan --worktable-path testwt.h5 --plot-path testgm.png
-# create the quadrant plot for a joint statistics file
-python -m jass plot-quadrant --worktable-path testwt.h5 --plot-path testqd.png
-```
-
+Detailed documentation, describing the setup, usage, and the architecture is available at http://statistical-genetics.pages.pasteur.fr/jass/
\ No newline at end of file