ChIP-seq workflow

Author:Menachem Sklarz Affiliation:Bioinformatics Core Facility Organization:National Institute of Biotechnology in the Negev, Ben Gurion University.

This workflow automates a standard ChIP-seq analysis.

Note

This workflow is based on a workflow kindly provided by Dr. Dena Leshkowitz of the Life Sciences Core Facilities, Weizmann Institute of Science.

Warning

The ChIP-seq workflow is in active development.

Steps:

1. Preparation and QA: a. Merging the reads into a single file per sample (merge). b. QC with fastqc (fastqc_html) c. Trimming with trimmomatic (trimmo) d. QC on trimmed reads with fastqc e. Adding the genome and the GTF file to the project (manage_types).
2. Mapping a. Creating a bowtie2 index for the genome (bowtie2_builder) a. Mapping the reads to the reference genome with bowtie2 (bowtie2_mapper) b. Conversion to sorted BAM with samtools (samtools) c. Sorting by name for bedGraphToBigWig with the Generic module. c. Converting to UCSC and IGV format (genomeCoverageBed, UCSC_BW_wig and IGV_count)
3. Finding ChIP peaks a. Peak calling is performed with macs2 callpeak (macs2_callpeak) b. Further analysis of the peaks is done with macs2 bdgcmp (macs2_bdgcmp)

Attention

In this workflow, we added the genome and GTF file via the parameter file. It is possible to add them via the sample file, as well.

Workflow Schema

Requires

• fastq files, either paired-end or single-end.
• A sample to control mapping (see Example sample lines below)

Programs required

• FastQC
• trimmomatic
• bowtie2
• samtools
• MultiQC
• macs2
• igvtools
• bedtools
• kentUtils

Tip

All programs can be installed with CODDA. See section Quick start with conda

Example of Sample File

Title       ChIP_project

#SampleID   Type    Path    lane
Sample1     Forward /path/to/Sample1_F1.fastq.gz 1
Sample1     Forward /path/to/Sample1_F2.fastq.gz 2
Sample1     Reverse /path/to/Sample1_R1.fastq.gz 1
Sample1     Reverse /path/to/Sample1_R2.fastq.gz 2
Sample2     Forward /path/to/Sample2_F1.fastq.gz 1
Sample2     Reverse /path/to/Sample2_R1.fastq.gz 1
Sample2     Forward /path/to/Sample2_F2.fastq.gz 2
Sample2     Reverse /path/to/Sample2_R2.fastq.gz 2

Sample_Control   Sample1:Sample2

Download

The workflow file is available here

Quick start with conda

For easy setup of the workflow with CONDA, use the following instructions:

1. Create and activate a conda environment with all the required programs:

   curl -LO https://raw.githubusercontent.com/bioinfo-core-BGU/neatseq-flow-modules/master/docs/source/Workflow_docs/ChIP_seq_conda.yaml
   conda env create -n ChIP_seq_WF -f ChIP_seq_conda.yaml
   source activate ChIP_seq_WF
   

2. Create a sample file. It should look like the file shown in Example of Sample File. Don’t forget to replace the sample names and file paths:

   Warning

   Make sure the file is TAB-delimited!

   Tip

   To get the full path to a file, use the following command:

   readlink -f <filename>
   

3. Get the parameter file with:

   curl -LO https://raw.githubusercontent.com/bioinfo-core-BGU/neatseq-flow-modules/master/Workflows/ChIP_seq.yaml
   

4. Run the workflow:

   1. Activate the NeatSeq-Flow conda environment. (See Installing NeatSeq-Flow)
   2. Execute the script generator and run the workflow. (See Running NeatSeq-Flow.)