nservant/nf-core-hic repository overview

Analysis of Chromosome Conformation Capture data (Hi-C).

⁠Introduction

This pipeline was originally set up from the HiC-Pro workflow⁠. It was designed to process Hi-C data from raw FastQ files (paired-end Illumina data) to normalized contact maps. The current version supports most protocols, including digestion protocols as well as protocols that do not require restriction enzymes such as DNase Hi-C. In practice, this workflow was successfully applied to many data-sets including dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.

Contact maps are generated in standard formats including HiC-Pro, and cooler for downstream analysis and visualization. Addition analysis steps such as compartments and TADs calling are also available.

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 / singularity containers making installation trivial and results highly reproducible.

⁠Pipeline summary

1. HiC-Pro data processing (HiC-Pro⁠)
   1. Mapping using a two steps strategy to rescue reads spanning the ligation sites (bowtie2⁠)
   2. Detection of valid interaction products
   3. Duplicates removal
   4. Generate raw and normalized contact maps (iced⁠)
2. Create genome-wide contact maps at various resolutions (cooler⁠)
3. Contact maps normalization using balancing algorithm (cooler⁠)
4. Export to various contact maps formats (HiC-Pro⁠, cooler⁠)
5. Quality controls (HiC-Pro⁠, HiCExplorer⁠)
6. Compartments calling (cooltools⁠)
7. TADs calling (HiCExplorer⁠, cooltools⁠)
8. Quality control report (MultiQC⁠)

⁠Quick Start

1. Install nextflow⁠ (>=20.04.0)

2. Install any of Docker⁠, Singularity⁠, Podman⁠, Shifter⁠ or Charliecloud⁠ 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/hic -profile test,<docker/singularity/podman/shifter/charliecloud/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/hic -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> --input '*_R{1,2}.fastq.gz' --genome GRCh37
   

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⁠Documentation

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

For further information or help, don't hesitate to get in touch on Slack⁠. You can join with this invite⁠.

⁠Credits

nf-core/hic was originally written by Nicolas Servant.

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

⁠Citation

If you use nf-core/hic for your analysis, please cite it using the following doi: 10.5281/zenodo.2669513⁠

You can cite the nf-core publication as follows:

In addition, references of tools and data used in this pipeline are as follows: