taoliulab/chip-seq-pipeline2

ENCODE ChIP-seq pipeline

ENCODE Transcription Factor and Histone ChIP-Seq processing pipeline

Introduction

This ChIP-Seq pipeline is based off the ENCODE (phase-3) transcription factor and histone ChIP-seq pipeline specifications (by Anshul Kundaje) in this google doc.

Features

• Portability: Support for many cloud platforms (Google/DNAnexus) and cluster engines (SLURM/SGE/PBS).
• User-friendly HTML report: tabulated quality metrics including alignment/peak statistics and FRiP along with many useful plots (IDR/cross-correlation measures).
  • Examples: HTML, JSON
• Genomes: Pre-built database for GRCh38, hg19, mm10, mm9 and additional support for custom genomes.

Installation

1. Install Caper. Caper is a python wrapper for Cromwell. Make sure that you have python3(> 3.4.1) installed on your system.

$ pip install caper

2. Read through Caper's README carefully.

3. Run a pipeline with Caper.

Running pipelines without Caper

Caper uses the cromwell workflow execution engine to run the workflow on the platform you specify. While we recommend you use caper, if you want to run cromwell directly without caper you can learn about that here.

DNAnexus

You can also run our pipeline on DNAnexus without using Caper or Cromwell. There are two ways to build a workflow on DNAnexus based on our WDL.

1. dxWDL CLI
2. DNAnexus Web UI

Conda

We no longer recommend Conda for resolving dependencies and plan to phase out Conda support. Instead we recommend using Docker or Singularity. You can install Singularity and use it for our pipeline with Caper (by adding --use-singularity to command line arguments). Please see this instruction.

Tutorial

Make sure that you have configured Caper correctly.

WARNING: Do not run Caper on HPC login nodes. Your jobs can be killed.

Run it. Due to --deepcopy all files (HTTP URLs) in examples/caper/ENCSR936XTK_subsampled_chr19_only.json will be recursively copied into Caper's temporary folder (--tmp-dir).

$ caper run chip.wdl -i examples/caper/ENCSR936XTK_subsampled_chr19_only.json --deepcopy --use-singularity

If you use Docker then replace --use-singularity with --use-docker.

$ caper run chip.wdl -i examples/caper/ENCSR936XTK_subsampled_chr19_only.json --deepcopy --use-docker

If you use Conda then remove --use-singularity from the command line and activate pipeline's Conda env before running a pipeline.

$ conda activate encode-chip-seq-pipeline
$ caper run chip.wdl -i examples/caper/ENCSR936XTK_subsampled_chr19_only.json --deepcopy

To run it on an HPC (e.g. Stanford Sherlock and SCG). See details at Caper's README.

Input JSON file

An input JSON file includes all genomic data files, input parameters and metadata for running pipelines. Always use absolute paths in an input JSON.

Input JSON file specification

How to organize outputs

Install Croo. Make sure that you have python3(> 3.4.1) installed on your system.

$ pip install croo

Find a metadata.json on Caper's output directory.

$ croo [METADATA_JSON_FILE]

Useful tools

There are some useful tools to post-process outputs of the pipeline.

qc_jsons_to_tsv

This tool recursively finds and parses all qc.json (pipeline's final output) found from a specified root directory. It generates a TSV file that has all quality metrics tabulated in rows for each experiment and replicate. This tool also estimates overall quality of a sample by a criteria definition JSON file which can be a good guideline for QC'ing experiments.

ENCODE downloader

This tool downloads any type (FASTQ, BAM, PEAK, ...) of data from the ENCODE portal. It also generates a metadata JSON file per experiment which will be very useful to make an input JSON file for the pipeline.