nf-HiChIP Pipeline

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Introduction

We have developed an nf-HiChIP pipeline that combines the analytical approach designed for ChIP-seq data processing (mapping, filtering, peak calling, coverage tracks calculations) with HiChIP-specific analysis (MAPS pipeline, Juric, Ivan, et al.). This pipeline enables users to conduct thorough and efficient analysis of multiple HiChIP datasets simultaneously, eliminating the requirement for additional ChIP-seq experiments. This workflow is based on the reference implementation of the method designed by Zofia Tojek. The original version is available here.

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Working with nf-HiChIP pipeline

Step 0. (optional)

You can get familiar with Nextflow options. From most important ones, -resume flag allows you to execute the pipeline from the last successful step. For more details see Nextflow documentation.

Step 1.

Docker image available:

https://hub.docker.com/repository/docker/mateuszchilinski/hichip-nf-pipeline/general

Command to run Docker image (use -v to bind folder with data):

docker run -v /path_to_your_data/:/data_in_container/ -it mateuszchilinski/hichip-nf-pipeline:latest bash

Step 2.

Required Files for Reference Folder (total 6 files) -

1. Reference fasta files -
    > Homo_sapiens_assembly38.fasta

2. BWA Reference Index files -
    > Homo_sapiens_assembly38.fasta.amb
    > Homo_sapiens_assembly38.fasta.ann
    > Homo_sapiens_assembly38.fasta.bwt
    > Homo_sapiens_assembly38.fasta.pac
    > Homo_sapiens_assembly38.fasta.sa

Step 3.

To run, use the command inside the container use:

/opt/nextflow run main.nf --design design.csv

Step 4.

Example for design.csv file:

sample	fastq_1	fastq_2	replicate	chipseq
S1	/data/SAMPLE1_1_R1.fastq.gz	/data/SAMPLE1_1_R2.fastq.gz	1	None
S1	/data/SAMPLE1_2_R1.fastq.gz	/data/SAMPLE1_2_R2.fastq.gz	2	None
S2	/data/SAMPLE2_1_R1.fastq.gz	/data/SAMPLE2_1_R2.fastq.gz	1	/data/SAMPLE2.narrowPeak
S2	/data/SAMPLE2_2_R1.fastq.gz	/data/SAMPLE2_2_R2.fastq.gz	2	/data/SAMPLE2.narrowPeak

Very important information regarding chipseq data!

If you don't have additional chipseq experiment results (in form of narrowPeaks), you need to put "None" (mind the capital letter!) in the last column - and the pseudo-chipseq will be called from HiChIP data. Also, remember that the pipeline is using chromosomes in "chrX" form. Peaks files need to be consistent with that as well.

If you have chipseq data, but don't have the peaks called yet, you can use ChIP-Seq processing part of the pipeline by calling:

/opt/nextflow run main_chipseq.nf --design design_chipseq.csv

In that case, the design_chipseq.csv should be in format of:

sample	fastq_1	fastq_2	input_1	input_2	replicate
S1	/data/SAMPLE1_1_R1.fastq.gz	/data/SAMPLE1_1_R2.fastq.gz	/data/SAMPLE1_INPUT_R1.fastq.gz	/data/SAMPLE1_INPUT_R2.fastq.gz	1
S1	/data/SAMPLE1_2_R1.fastq.gz	/data/SAMPLE1_2_R2.fastq.gz	/data/SAMPLE1_INPUT_R1.fastq.gz	/data/SAMPLE1_INPUT_R2.fastq.gz	2
S2	/data/SAMPLE2_1_R1.fastq.gz	/data/SAMPLE2_1_R2.fastq.gz	/data/SAMPLE2_INPUT_R1.fastq.gz	/data/SAMPLE2_INPUT_R2.fastq.gz	1
S2	/data/SAMPLE2_2_R1.fastq.gz	/data/SAMPLE2_2_R2.fastq.gz	/data/SAMPLE2_INPUT_R1.fastq.gz	/data/SAMPLE2_INPUT_R2.fastq.gz	2

If you want to call chipseq peaks first, you can use main_chipseq.nf with exactly the same parameters. The input should be exactly the same for all replicates in a given sample.

Step 5.

The parameters of the pipeline can be found in the following table. All of them are optional:

Parameter	Description	Default
--ref	Reference genome for the analysis.	/workspaces/hichip-nf-pipeline/ref/Homo_sapiens_assembly38.fasta
--outdir	Folder with the final results.	results
--design	.csv file containing information about samples and replicates.	/workspaces/hichip-nf-pipeline/design_high.csv
--chrom_sizes	Sizes of chromosomes for the specific reference genome.	/workspaces/hichip-nf-pipeline/hg38.chrom.sizes
--threads	Threads to use in each task.	4
--mem	Memory to use (in GB) for all samtools tasks (per-sample - e.g., 4 samples with 4 threads with 4GB would result in consumption of 64GB of memory).	16
--mapq	MAPQ for MAPS.	30
--peak_quality	Quality parameter (q-value (minimum FDR) cutoff) for MACS3.	0.05
--genome_size	Genome size string for MACS3.	hs

Step 5.

For Post-processing and figure recreation, please follow the scripts in the folder post_processing

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Citation

If you use nf-HiChIP in your research (the idea, the algorithm, the analysis scripts, or the supplemental data), please give us a star on the GitHub repo page and cite our paper as follows:

• Official version --
• Preprint bioRxiv --

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