lvelosuarez / agnostos-wf Goto Github PK

The workflow is still under development and it is subject to change. No guarentee is made regarding the functioning of the workflow and the accuracy of the results. Please, conctact us in case you are interested in using it.

The "agnostos-wf" snakemake workflow was developed using/runs in the de.NBI Cloud. We used a cluster setup with 10 nodes of 28 cores and 252 G of memory each. The cluster was build using BiBiGrid and it is using SLURM as Grid Batch Scheduler.

1. Clone the repository: git clone https://github.com/functional-dark-side/agnostos-wf and cd agnostos-wf/

2. Run the installation script installation_script.sh (sh installation_script.sh).

3. Check the config files in the config/ folder. Change the programs (binaries) and output paths to your designated folders.

4. Check that you have the required external DBs listed in the config.yaml file (in the "databases/" folder). In case you miss some of them, you can find the instructions for the dowload in download_DBs.sh. If you want to download all needed databases simply run sh download_DBs.sh (be patient this may take a while...).

When everything is set...

1. DB-creation module: Start from a set of genomic/metagenomic contigs in fasta format and retrieve a database of categorised gene clusters and cluster communities.

cd db_creation/
snakemake --use-conda -j 100 --cluster-config config/cluster.yaml --cluster "sbatch --export=ALL -t {cluster.time} -c {threads} --ntasks-per-node {cluster.ntasks_per_node} --nodes {cluster.nodes} --cpus-per-task {cluster.cpus_per_task} --job-name {rulename}.{jobid} --partition {cluster.partition}" -R --until workflow_report

2. DB-Update module: Add your genomic/metagenomic contigs or genes to the agnostosDB dataset is stored in Figshare (https://doi.org/10.6084/m9.figshare.12459056) and publicy available for download. In case you cannot download the whole dataset, seen to the large size of many of the files, the workflow will download the necessary files for each step and it will then remove them. A description of the agnostosDB files can be found in the AgnostosDB_README.md.

• The DB-update workflow is in the db_update/ folder. To run it, you just need to enter the folder, modify the config.yaml and config_communities.yml files specifying your input data and the output paths, and then run the command:

cd db_update/
snakemake -s Snakefile --use-conda -j 100 --cluster-config config/cluster.yaml --cluster "sbatch --export=ALL -t {cluster.time} -c {threads} --ntasks-per-node {cluster.ntasks_per_node} --nodes {cluster.nodes} --cpus-per-task {cluster.cpus_per_task} --job-name {rulename}.{jobid} --partition {cluster.partition}" -R --until workflow_report

NB: If you want to run the DB-update module on the results of the DB-creation module, first copy/move the cluster database in the final DB-update results:

mv db_creation/mmseqs_clustering db_creation/clusterDB_results/

Output

The output of these 2 modules is described in the Output_README.md.

Set of 10K contigs to test the DB-creation module and 5K contigs to test the DB-update module of the workflow. The test-dataset can be downloaded from Figshare as follows:

mkdir -p agnostos_test
cd agnostos_test
wget https://ndownloader.figshare.com/files/25473332 -O db_creation_data.tar.gz
tar -xzvf db_creation_data.tar.gz

wget https://ndownloader.figshare.com/files/25473335 -O db_update_data.tar.gz
tar -xzvf db_update_data.tar.gz

A brief description of the dataset is available on Figshare.

Profile-search: the profile-search vs the AgnostosDB cluster HMM profiles database is not part of the Snakemake workflow. However, if you want to search your set of genes against our profiles you just need to dowload the profile DB from here. The scripts can be found in the Profile_search/ folder. To run the search you just need the following command:

Profile_search/profile_search.sh --query your-genes.fasta --clu_hmm clu_hmm_db --clu_cat cluster_ids_categ.tsv --info your-genes_add_info.tsv --mmseqs /path/to/mmseqs --threads num-threads

The "--info" file is optional, and should be a table with the correspondence of the genes to the contigs and/or genomes/MAGs/samples. The format should be gene - genome (or sample_ID) etc.

To lern more about what we are doing check out our website dark.metagenomics.eu.

Vanni, C., Schechter, M., Acinas, S., Barberán, A., Buttigieg, P. L., Casamayor, E. O., Delmont, T. O., Duarte, C. M., Murat Eren, A., Finn, R., Kottmann, R., Mitchell, A., Sanchez, P., Siren, K., Steinegger, M., Glöckner, F. O., & Fernandez-Guerra, A. (2020). Light into the darkness: Unifying the known and unknown coding sequence space in microbiome analyses. In bioRxiv (p. 2020.06.30.180448). https://doi.org/10.1101/2020.06.30.180448