B-GUT-decontamination

Snakemake pipeline to decontaminate genomes to be included in a kraken2 database.

Example of the pipeline run in a folder containing 4 genomes [An example of one of these genomes is provided in the folder "Example_genomes"]

Installation: Singularity image

1. Marenostrum5

You will find the .sif file at ~/current/okhannous/Decontamination_fungal_database/my_singularity.sif

2. Local use

You will need to build and deploy the Singularity image. First you have to download Singularity. Details of how to do it: HERE

Using the provided Dockerfile and Makefile files (present in the current github resources) run:

make singularity-image

This will create the "my_singularity.sif", ready to be used with our snakemake pipeline.

How to run the pipeline using the Singularity image

Here there is an example of command to run the pipeline.

singularity exec --cleanenv ~/my_singularity.sif snakemake -s bgut_decontam.smk all --cores 48

In the .smk file there is indicated the path to the .sif image.

You can find a template job to run the pipeline in the cluster: "bgut_decontam.job"

Note that the pipeline is fast but requires high mem nodes because of the kraken2 step. You can have a debug interaction session and run it there by:

salloc -A user_account -q gp_debug --exclusive --constraint=highmem
singularity exec --cleanenv ~/my_singularity.sif snakemake -s bgut_decontam.smk all --cores 488

Of note, the pipeline uses a configuration file to specificy paths, prefixes, suffixes, and the Kraken2 database. An example configuration file is provided (config.yaml) in this repository. You should modify it according to your specific needs and setup

Citations / Acknowledgments

Snakemake

Mölder, F., Jablonski, K. P., Letcher, B., Hall, M. B., Tomkins-Tinch, C. H., Sochat, V., Forster, J., Lee, S., Twardziok, S. O., Kanitz, A., Wilm, A., Holtgrewe, M., Rahmann, S., Nahnsen, S., & Köster, J. (2021). Sustainable data analysis with Snakemake. F1000Research, 10, 33. https://doi.org/10.12688/f1000research.29032.2

Kraken2

Wood, D. E., Lu, J., & Langmead, B. (2019). Improved metagenomic analysis with Kraken 2. Genome biology, 20(1), 257. https://doi.org/10.1186/s13059-019-1891-0

Tiara

Karlicki, M., Antonowicz, S., & Karnkowska, A. (2022). Tiara: deep learning-based classification system for eukaryotic sequences. Bioinformatics (Oxford, England), 38(2), 344–350. https://doi.org/10.1093/bioinformatics/btab672

Seqkit

Shen, W., Sipos, B., & Zhao, L. (2024). SeqKit2: A Swiss army knife for sequence and alignment processing. iMeta, 3(3), e191. https://doi.org/10.1002/imt2.191