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ChIP-Seq Peak Calling

Authors Xing Tang, Yong Cheng
Publication N/A (not published)
Technical Support Contact Us

The ChIP-Seq Peak Calling workflow follows ENCODE best practices to call broad or narrow peaks on Illumina-generated ChIP-Seq data. Here, a Gzipped FastQ file from an Immunoprecipitation (IP) experiment is considered the "case sample file" and a Gzipped FastQ file from a control experiment is considered the "control sample file". The pipeline can run on matched case/control samples (recommended for better results) or just a case sample.



Name Type Description Example
FastQ files (required if using FastQ inputs) Input file Gzipped FastQ files generated by experiment. Sample_R1.fastq.gz and Sample_R2.fastq.gz


Name Format Description
BED file .bed Peak calls
Binary file .bb Binary format for BED file
BigWig file .bw Shows read coverage
Metrics file .txt Shows mapping and duplication rate
Cross correlation plot .pdf Quality plot showing if the forward and reverse reads tend to be centered around binding sites.


  1. The reads of the FastQ file(s) are aligned to the specified reference genome.
  2. The aligned reads are then post-processed based on best-practice QC techniques (removing multiple mapped reads, removing duplicated reads, etc).
  3. Peaks are called by SICER (broad peak analysis) or MACS2 (narrow peak analysis).
    • Qualified peaks will be output as BED (.bed) and big BED (.bb) files.
    • The coverage information will be output as a bigWig (.bw) file.
    • A cross correlation plot and general metrics file are generated to help check the quality of experiment.

Getting started

To get started, you need to navigate to the ChIP-Seq tool page. You'll need to click the "Start" button in the left hand pane. This creates a cloud workspace in DNAnexus with the same name as the tool. After this, you will be able to upload your input files to that workspace.


If you can't see the "Start" button, one of these two scenarios is likely the case:

  • You see three buttons on the left sidebar instead of one. In this case, you've already clicked the "Start" button previously, and a cloud workspace has already been created for you. In this case, you're good! You can move on to the next section.
  • If you cannot see any buttons on the left side, you probably have not logged in yet. If you see a sentence that says "Log in to launch this tool", simply login and try again.

If neither of these are the case and you still can't click "Start", contact us.

Uploading data

The ChIP-Seq Peak Caller takes Gzipped FastQ files generated from an IP experiment as input. You can upload your input FastQ files by using the data transfer application or by uploading them through the command line. Both of the guides linked here will contain more details on how to upload data using that method, so we defer to those guides here.


If you plan to upload data through the St. Jude Cloud Data Transfer application (recommended), you can click the "Upload Data" button in the left panel. If you have not already downloaded the app, do so by clicking "Download app". Once you have the app, you can click "Open app" to open the app with the tool's cloud workspace already opened and ready to drag-and-drop files into it!

For more information, check out the data transfer application guide.

Running the tool

Once you've uploaded data to your cloud workspace, click "Launch Tool" on the tool's landing page. A dropdown will present the different presets for running the ChIP-Seq workflow. You'll need to decide (1) whether you'd like to run broad/narrow peak calling and (2) whether you have a case sample and a control sample (preferred) or just a case sample. This will determine which preset you should click in this dropdown. There are various other parameters that you can set, but they are covered in further sections of this guide.

Broad vs. narrow peak calling

Choosing between broad and narrow peak calling depends on the experiment design. The following are good rules of thumb for choosing between the two configurations. If you are not sure which configuration to use, please consult with an expert at your institution or contact us.

Narrow Peak Calling

If your target protein is a transcription factor, you should probably choose narrow peak calling. You can also try the narrow peak calling workflows for the following histone marks:

  • H3K4me3
  • H3K4me2
  • H3K9-14ac
  • H3K27ac
  • H2A.Z

Broad Peak Calling

You should try the broad peak calling workflows for the following histone marks:

  • H3K36me3
  • H3K79me2
  • H3K27me3
  • H3K9me3
  • H3K9me1

Special Cases

In some scenarios, H3K4me1, H3K9me2 and H3K9me3 might behave between narrow and broad shape, you might need to look into each peak region and consult experts.


If your fragment size is less than 50 base pairs, please refer to the frequently asked questions.

Selecting parameters

There are a number of other parameters that can be customized. To see the options available, click the gear cog next to the "Parameter Wrapper" substep.

The following are the parameters that can be set, a short description of each parameter, and an example value. If you have questions, please contact us.

Parameter Name Description Example
Output prefix (required) A name used a prefix for all outputs in the run SAMPLE1
Reference genome (required) Supported reference genome from one of hg19, GRCh38, mm9, mm10, dm3 GRCh38
Output bigWig Whether or not to include a bigwig file in the output True
Remove blacklist peaks Whether or not to remove known problem areas True
Fragment length Hardcoded fragment length of your reads. 'NA' for auto-detect. NA


Please be aware of the following stumbling points when setting parameters:

  • Do not use spaces anywhere in your input file names, your output prefix, or any of the other parameters. This is generally bad practice and doesn't play well with the pipeline (consider using "_" instead).
  • Do not change the output directory when you run the pipeline. At the top of parameter input page, there is a text box that allows you to change the output folder. Please ignore that setting. You only need to specify an output prefix as described above. All of the results will be put under /Results/[OUTPUT_PREFIX].

Hooking up inputs

Next, you'll need to hook up the FastQ files you uploaded in the upload data section. You can do this by clicking on the ChIP Reads and Control Reads slots and selecting the respective files. If you are not doing a case/control run, you only need to hook up the case sample.

Starting the workflow

Once your input files are hooked up, you should be able to start the workflow by clicking the "Run as Analysis..." button in the top right hand corner of the workflow dialog.


If you cannot click this button, please ensure that:

If you're still have trouble, please contact us and include a screenshot of the workflow screen above.

Monitoring run progress

Once you have started one or more ChIP-Seq runs, you can safely close your browser and come back later to check the status of the jobs. To do this, navigate to the tool's landing page. Next, click "View Results" then select the "View Running Jobs" option. You will be redirected to the job monitoring page. Each job you kicked off gets one row in this table.

You can click the "+" on any of the runs to check the status of individual steps of the ChIP-Seq pipeline. Other information, such as time, cost of individual steps in the pipeline, and the job logs can be accessed by clicking around the sub-items.


Power users can refer to the DNAnexus Monitoring Executions Documentation for advanced capabilities for monitoring jobs.

Interactive visualizations

Today, the ChIP-Seq pipeline does not produce an interactive visualization. We are working on adding this! In the meantime, you can view the cross-correlation plot(s) as outlined in the sections below.

Finding the raw results files

Navigate to the tool's landing page. In the left hand pane, click "View Results" then "View Results Files". You will be taken to the filesystem view of your cloud workspace. This is similar to the filesystem on your computer, and you can do many common operations such as deleting, renaming, and moving files. To access ChIP-Seq results, you should click on the Results folder, then select the output folder name you gave in the selecting parameters part of the guide.

Interpreting results

For the ChIP-Seq pipeline, every pipeline run outputs a README.doc file which contains the latest information on which results are included. You can refer to that file for the most up to date information on raw outputs.

Frequently asked questions

If you have any questions not covered here, feel free to contact us.

Q: Should I choose narrow peak calling pipeline or broad peak calling pipeline?

A. We built two workflows: one for narrow peak calling and another broad peak calling. If your target protein is a transcription factor, please use narrow peak calling workflow. For histone marks H3K4me3, H3K4me2, H3K9-14ac, H3K27ac and H2A.Z, you could try narrow peak calling workflow. For histone marks H3K36me3, H3K79me2, H3K27me3, H3K9me3 and H3K9me1, you could try broad peak calling workflow. In some scenario, H3K4me1, H3K9me2 and H3K9me3 might behave between narrow and broad shape, you might need to look into each peak region and consult experts.

Q. What to do if your fragment size is less than 50 base pairs?

A. We estimate fragment size from the data based on the cross correlation plot. Usually the fragment size is above 50bp. If the estimated fragment size lower than 50bp, the workflow will stop at the peak calling stage (MACS2/SICER) after BWA mapping finishes. You can rerun the analysis with a specified fragment length.