diff --git a/README.md b/README.md
index a058f7225091cc706704a6b949f61ae2a774c9ee..3ea1c2a84d846eade4939132ab212bde02024556 100644
--- a/README.md
+++ b/README.md
@@ -5,6 +5,7 @@
 Name | Description
 ---- | -----------
 [Data simulation](simulation/) | Generate simulated metagenomics data for benchmarking
+[Sunbeam](sunbeam/) | How to use sunbeam at Pasteur on TARS
 
 ## Projects and repository
 
diff --git a/simulation/README.md b/simulation/README.md
index 5904e19592bf64c0129a39f6e0791f263865ca2a..1959af1caeb06fb3a03a9b224ec23e140ff2b34b 100644
--- a/simulation/README.md
+++ b/simulation/README.md
@@ -24,6 +24,9 @@ make the process a bit faster. Files can be found in the `example/` directory.
 All the path are preceded by the `/input` directory since we are going to mount our config
 files into this directory.
 
+> **Warning** Generated paired-end reads are in one unique `fastq` file that need to be
+splitted in `_R1` and `_R2` files.
+
 ### With docker
 
 ```bash
@@ -71,13 +74,10 @@ output_directory=out
 temp_directory=/tmp
 gsa=True                # whether a gold standard assembly should be created
 pooled_gsa=True         # whether a pooled gold standard over all samples is created
-anonymous=False         # whether the output is anonymized
+anonymous=True          # whether the output is anonymized (reads from genomes are shuffled)
 compress=1              # 0 is for no compression, 9 is maximum compression
 ```
 
-Since we do not need the data for a challenge, we can switch off the anonymous part of the process. _For the moment it seems that it [does not work without anonymization]
-(https://github.com/CAMI-challenge/CAMISIM/issues/64) so it is better to keep the `anonymous` flag to `True`_.
-
 #### Read Simulator
 
 ```ini
diff --git a/sunbeam/README.md b/sunbeam/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..c53f01f53f0c852f22dd0a81083ef8d1bc69783f
--- /dev/null
+++ b/sunbeam/README.md
@@ -0,0 +1,42 @@
+# Sunbeam
+
+[Sunbeam](https://github.com/sunbeam-labs/sunbeam) is a pipeline written in snakemake
+that simplifies and automates many of the steps in metagenomic sequencing analysis.
+
+Here is a brief note to help you use sunbeam at Pasteur on TARS. You can also read the
+full [documentation](https://sunbeam.readthedocs.io/en/latest/?badge=latest).
+
+## Install
+
+Procedure is very similar to what you would do locally. Install deal with conda install
+if you are not using conda. If you want the latest available version:
+
+```bash
+git clone https://github.com/eclarke/sunbeam
+cd sunbeam
+bash install.sh
+source activate sunbeam
+```
+
+> **Warning** You need internet access to do that so you need to perform install on
+the head of submission.
+
+## Run sunbeam
+
+You can follow the [documentation](https://sunbeam.readthedocs.io/en/latest/?badge=latest)
+for the initialization of your analysis directory. This will generate a config file in this
+directory that we will call `sunbeam_config.yml`.
+
+We also consider that we are working on the dedicated `atm` queue.
+
+Once done you can run sunbeam for the quality control on tars:
+
+```bash
+sbatch --qos=atm -p atm -c 1 sunbeam run --configfile sunbeam_config.yml all_qc --jobs 10 --cluster-config cluster.yml --cluster "sbatch --qos=atm -p atm -c {threads}"
+```
+
+Refer to the [documentation](https://sunbeam.readthedocs.io/en/latest/?badge=latest) to
+see all the different pipelines available.
+
+You can also personalize required resources by adding a `cluster.yml` file as described in
+this [page](https://gitlab.pasteur.fr/metagenomics/snakemake/tree/master/workflows#using-on-tars)