Gene-by-gene outbreaks analysis pipeline using cgMLST schemas..
nf-core/genebygenebact is a bioinformatics best-practise analysis pipeline for
The pipeline is built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.
-
Install
nextflow
(>=20.04.0
) -
Install any of
Docker
,Singularity
,Podman
,Shifter
orCharliecloud
for full pipeline reproducibility (please only useConda
as a last resort; see docs) -
Download the pipeline and test it on a minimal dataset with a single command:
nextflow run nf-core/genebygenebact -profile test,<docker/singularity/podman/shifter/charliecloud/conda/institute>
Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use
-profile <institute>
in your command. This will enable eitherdocker
orsingularity
and set the appropriate execution settings for your local compute environment. -
Start running your own analysis!
nextflow run nf-core/genebygenebact -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37
See usage docs for all of the available options when running the pipeline.
By default, the pipeline currently performs the following:
- Sequencing quality control (
FastQC
) - Overall pipeline run summaries (
MultiQC
)
The nf-core/genebygenebact pipeline comes with documentation about the pipeline: usage and output.
nf-core/genebygenebact was originally written by Esperanza López López.
We thank the following people for their extensive assistance in the development of this pipeline:
If you would like to contribute to this pipeline, please see the contributing guidelines.
For further information or help, don't hesitate to get in touch on the Slack #genebygenebact
channel (you can join with this invite).
You can cite the nf-core
publication as follows:
The nf-core framework for community-curated bioinformatics pipelines.
Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.
Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
In addition, references of tools and data used in this pipeline are as follows: