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> Andrews, S. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data [Online].- [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/)
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> Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924.
[](https://github.com/nf-core/chipseq/actions/workflows/ci.yml)
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</h1>[](https://github.com/nf-core/chipseq/actions/workflows/ci.yml)
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[](https://github.com/nf-core/chipseq/actions/workflows/linting.yml)[](https://nf-co.re/chipseq/results)[](https://doi.org/10.5281/zenodo.XXXXXXX)
2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))
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<!-- TODO nf-core: Fill in short bullet-pointed list of the default steps in the pipeline -->1. Read QC ([`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/))2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/))
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## Usage
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> [!NOTE]
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> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow.Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.
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> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow.Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data.
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<!-- TODO nf-core: Describe the minimum required steps to execute the pipeline, e.g. how to prepare samplesheets.
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Explain what rows and columns represent. For instance (please edit as appropriate):
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## Citations
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<!-- TODO nf-core: Add citation for pipeline after first release. Uncomment lines below and update Zenodo doi and badge at the top of this file. -->
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<!-- If you use nf-core/chipseq for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) -->
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<!-- TODO nf-core: Add bibliography of tools and data used in your pipeline -->
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<!-- If you use nf-core/chipseq for your analysis, please cite it using the following doi: [10.5281/zenodo.XXXXXX](https://doi.org/10.5281/zenodo.XXXXXX) --><!-- TODO nf-core: Add bibliography of tools and data used in your pipeline -->
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An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file.
Copy file name to clipboardExpand all lines: docs/output.md
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The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps:
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-[FastQC](#fastqc) - Raw read QC
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-[MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline
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-[FastQC](#fastqc) - Raw read QC- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline
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-[Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution
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### FastQC
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</details>
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[FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the [FastQC help pages](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/).
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### MultiQC
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[FastQC](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) gives general quality metrics about your sequenced reads. It provides information about the quality score distribution across your reads, per base sequence content (%A/T/G/C), adapter contamination and overrepresented sequences. For further reading and documentation see the [FastQC help pages](http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/).### MultiQC
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<detailsmarkdown="1">
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<summary>Output files</summary>
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[MultiQC](http://multiqc.info) is a visualization tool that generates a single HTML report summarising all samples in your project. Most of the pipeline QC results are visualised in the report and further statistics are available in the report data directory.
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Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see <http://multiqc.info>.
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### Pipeline information
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Results generated by MultiQC collate pipeline QC from supported tools e.g. FastQC. The pipeline has special steps which also allow the software versions to be reported in the MultiQC output for future traceability. For more information about how to use MultiQC reports, see <http://multiqc.info>.### Pipeline information
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> [!IMPORTANT]
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> We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported.
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The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to check if your system is suported, please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).
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The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to check if your system is supported, please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation).
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Note that multiple profiles can be loaded, for example: `-profile test,docker` - the order of arguments is important!
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They are loaded in sequence, so later profiles can overwrite earlier profiles.
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