home.md

@@ -48,34 +48,38 @@ conda activate snakemake_rapidrun
 You are ready to run the analysis !
 
 
-## Download data
-
-
-The complete data set can be downloaded and stored into [resources/tutorial](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_obitools/-/tree/master/resources/tutorial) folder with the following command:
+## Download example data
 
 ```
-wget -c https://gitlab.mbb.univ-montp2.fr/edna/tutorial_metabarcoding_data/-/raw/master/tutorial_rapidrun_data.tar.gz -O - | tar -xz -C ./resources/tutorial/
+curl -JLO http://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_data_test/-/raw/master/test_rapidrun_data.tar.gz; tar zfxz test_rapidrun_data.tar.gz -C resources/test/
 ```
-* Data is downloaded at [resources/tutorial](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/tree/master/resources/tutorial)
-* This is a tiny subset of a real metabarcoding analysis in rapidrun format
+* Data is downloaded at [resources/test/test_rapidrun_data](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/tree/master/resources/tutorial)
+*  this folder contains a reference database for 4 markers (Teleo01; Mamm01; Vert01; Chond01), NGS metabarcoding raw data, required metadata to handle demultiplexing on RAPIDRUN format
 
 
-# Run the workflow
+## Run the workflow
 
-Simply type the following command to process data (estimated time: 25 minutes)
+Simply type the following command to process example data
 
 ```
-bash main.sh config/config_tutorial.yaml 8
+snakemake --configfile config/config_test_rapidrun.yaml --cores 4 --use-conda
 ```
 
+* The first argument `--configfile` [config/config_test_rapidrun.yaml](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/blob/master/config/config_test_rapidrun.yaml) contains parameters to apply
+* The second argument `--cores` **4** is the number of CPU cores you want to allow the system uses to run the whole workflow
+* The third argument `--use-conda` is only necessary if you installed the program and its dependencies using conda
+
+
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+______________________________________________________
+
 
-* This will generate OTU occ:urences tables into [results/06_assignment/04_table](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/tree/master/results/06_assignment/04_table)
-* The first argument [config/config_tutorial.yaml](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/blob/master/config/config_tutorial.yaml) contains mandatory parameters information
-* The second argument **8** is the number of CPU cores you want to allow the system uses to run the whole workflow
 
-# To go further
 
-Please check the [wiki](https://gitlab.mbb.univ-montp2.fr/edna/snakemake_rapidrun_swarm/-/wikis/home).
 
 
 # Cluster MBB