Complete analysis workflow for single-cell/nuclei RNA-sequencing data..

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.

1. Install nextflow

2. Install any of Docker, Singularity or Podman for full pipeline reproducibility (please only use Conda as a last resort; see docs)

3. Download the pipeline and test it on a minimal dataset with a single command:

   nextflow run nf-core/scflow -profile test,<docker/singularity/podman/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 either docker or singularity and set the appropriate execution settings for your local compute environment.

4. Start running your own analysis!

   nextflow run nf-core/scflow -profile <docker/singularity/podman/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37

See usage docs for all of the available options when running the pipeline.

The nf-core/scflow pipeline comes with documentation about the pipeline: usage and output.

nf-core/scflow was originally written by Dr Combiz Khozoie.

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 #scflow 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. ReadCube: Full Access Link