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[](https://github.com/nf-core/hic/actions?query=workflow%3A%22nf-core+CI%22)
[](https://docs.conda.io/en/latest/)
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[](https://www.docker.com/)
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[](https://sylabs.io/docs/)
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[](https://nf-co.re/hic/results)[](https://doi.org/10.5281/zenodo.XXXXXXX)
[](https://docs.conda.io/en/latest/)
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[](https://www.docker.com/)
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[](https://sylabs.io/docs/)
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[](https://tower.nf/launch?pipeline=https://github.com/nf-core/hic)
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[](https://nfcore.slack.com/channels/hic)
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[](https://twitter.com/nf_core)
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[](https://www.youtube.com/c/nf-core)
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[](https://nfcore.slack.com/channels/hic)[](https://twitter.com/nf_core)[](https://www.youtube.com/c/nf-core)
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## Introduction
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**nf-core/hic** is a bioinformatics best-practice analysis pipeline for Analysis of Chromosome Conformation Capture data (Hi-C).
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The pipeline is built using [Nextflow](https://www.nextflow.io), a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It uses Docker/Singularity containers making installation trivial and results highly reproducible. The [Nextflow DSL2](https://www.nextflow.io/docs/latest/dsl2.html) implementation of this pipeline uses one container per process which makes it much easier to maintain and update software dependencies. Where possible, these processes have been submitted to and installed from [nf-core/modules](https://github.com/nf-core/modules) in order to make them available to all nf-core pipelines, and to everyone within the Nextflow community!
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On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/hic/results).
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On release, automated continuous integration tests run the pipeline on a full-sized dataset on the AWS cloud infrastructure. This ensures that the pipeline runs on AWS, has sensible resource allocation defaults set to run on real-world datasets, and permits the persistent storage of results to benchmark between pipeline releases and other analysis sources.The results obtained from the full-sized test can be viewed on the [nf-core website](https://nf-co.re/hic/results).
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## Pipeline summary
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2. Install any of [`Docker`](https://docs.docker.com/engine/installation/), [`Singularity`](https://www.sylabs.io/guides/3.0/user-guide/) (you can follow [this tutorial](https://singularity-tutorial.github.io/01-installation/)), [`Podman`](https://podman.io/), [`Shifter`](https://nersc.gitlab.io/development/shifter/how-to-use/) or [`Charliecloud`](https://hpc.github.io/charliecloud/) for full pipeline reproducibility _(you can use [`Conda`](https://conda.io/miniconda.html) both to install Nextflow itself and also to manage software within pipelines. Please only use it within pipelines as a last resort; see [docs](https://nf-co.re/usage/configuration#basic-configuration-profiles))_.
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3. Download the pipeline and test it on a minimal dataset with a single command:
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```console
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```bash
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nextflow run nf-core/hic -profile test,YOURPROFILE --outdir <OUTDIR>
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```
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description: "Suggested text and references to use when describing pipeline usage within the methods section of a publication."
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section_name: "nf-core/hic Methods Description"
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section_href: "https://github.com/nf-core/hic"
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plot_type: "html"
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## TODO nf-core: Update the HTML below to your prefered methods description, e.g. add publication citation for this pipeline
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## You inject any metadata in the Nextflow '${workflow}' object
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data: |
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<h4>Methods</h4>
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<p>Data was processed using nf-core/hic v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (<a href="https://doi.org/10.1038/s41587-020-0439-x">Ewels <em>et al.</em>, 2020</a>).</p>
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<p>The pipeline was executed with Nextflow v${workflow.nextflow.version} (<a href="https://doi.org/10.1038/nbt.3820">Di Tommaso <em>et al.</em>, 2017</a>) with the following command:</p>
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<pre><code>${workflow.commandLine}</code></pre>
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<h4>References</h4>
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<ul>
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<li>Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. <a href="https://doi.org/10.1038/nbt.3820">https://doi.org/10.1038/nbt.3820</a></li>
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<li>Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. <a href="https://doi.org/10.1038/s41587-020-0439-x">https://doi.org/10.1038/s41587-020-0439-x</a></li>
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</ul>
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<div class="alert alert-info">
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<h5>Notes:</h5>
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<ul>
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${nodoi_text}
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<li>The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!</li>
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<li>You should also cite all software used within this run. Check the "Software Versions" of this report to get version information.</li>
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