laurencekuhl/shrnacount2 repository overview

Count of shrna.

⁠Introduction

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.

⁠Quick Start

1. Install nextflow⁠

2. Install either Docker⁠ or Singularity⁠ 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/shrnacount -profile test,<docker/singularity/conda/institute>
   

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   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/shrnacount -profile <docker/singularity/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37
   

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

⁠Documentation

The nf-core/shrnacount pipeline comes with documentation about the pipeline which you can read at https://nf-core/shrnacount/docs⁠ or find in the docs/ directory⁠.

⁠Credits

nf-core/shrnacount was originally written by Laurence Kuhlburger.

⁠Contributions and Support

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 #shrnacount channel⁠ (you can join with this invite⁠).

⁠Citation

You can cite the nf-core publication as follows: