Installation & Setup¶

Epi-Flow is designed to be lightweight and portable, but it relies on a set of standard, powerful bioinformatics tools. This guide will walk you through the recommended setup process.

Dependencies¶

Before installation, it’s helpful to know what software the pipeline orchestrates. Epi-Flow is essentially a “conductor” for these tools:

Tool	Purpose in Epi-Flow
FastQC	Gathers raw read quality metrics.
Cutadapt	Trims adapter sequences and low-quality bases.
Bowtie2	Performs fast and memory-efficient read alignment.
Samtools	The toolkit for manipulating alignment (BAM) files.
Picard	Marks PCR duplicates and collects alignment metrics.
Bedtools	Handles genomic interval operations (e.g., blacklist filtering).
MACS3	The primary peak caller for identifying signal enrichment.
SEACR	A specialized peak caller for low-background CUT&RUN/Tag data.
DeepTools	Generates normalized signal tracks (bigWig) and QC plots.
MultiQC	Aggregates all QC reports into a single interactive HTML file.

Recommended Method: Using Conda / Mamba¶

The most reliable and reproducible way to manage these dependencies is with a dedicated Conda environment. This isolates the pipeline’s software from your system’s other tools, preventing version conflicts.

We recommend using Mamba, a fast, drop-in replacement for Conda. The commands are interchangeable.

Step 1: Create a Project Directory¶

First, create a directory for your project and navigate into it.

mkdir my_chromatin_analysis
cd my_chromatin_analysis

Step 2: Create the Conda Environment¶

This is the most critical step. We provide an environment.yml file for a simple, one-command installation.

Create a file named environment.yml in your project directory and paste the following content into it:

# environment.yml for Epi-Flow
name: epiflow
channels:
  - bioconda
  - conda-forge
dependencies:
  - fastqc
  - cutadapt
  - bowtie2
  - samtools>=1.16
  - picard
  - bedtools
  - macs3
  - seacr
  - deeptools
  - multiqc

Create the environment from this file using Mamba or Conda. Mamba is significantly faster.
```
# Using Mamba (Recommended)
mamba env create -f environment.yml

# Or, using Conda
conda env create -f environment.yml
```
This command will download and install all the specified tools into an isolated environment named epiflow.

Step 3: Get the Epi-Flow Script¶

Clone the Epi-Flow repository from GitHub.

git clone https://github.com/zqzneptune/epi-flow.git

This will create an epi-flow directory containing the pipeline script.

Step 4: Verify the Installation¶

Now, let’s confirm everything is working correctly.

Activate the Conda environment:
```
mamba activate epiflow
```
Your command prompt should now be prefixed with (epiflow).
Make the script executable: This command gives your system permission to run the script. You only need to do this once.
```
chmod +x ./epi-flow/epi_flow.sh
```
Run the help command:
```
./epi-flow/epi_flow.sh --help
```

If the installation was successful, you will see the pipeline’s usage information and a list of all available parameters printed to your screen. You are now ready to run your analysis!

Alternative: Using HPC Modules¶

If you are on an HPC cluster and cannot use Conda, you can use the module system. Note: This method is less reproducible as module versions can vary between systems.

Find the required modules on your system. Commands like module avail or module spider can help.

Load the modules. The exact names will differ, but the command will look something like this:

# Example module loading script for an HPC
module load fastqc/0.11.9
module load cutadapt/4.1
module load bowtie2/2.4.5
module load samtools/1.16.1
module load picard/2.27.5
module load bedtools/2.30.0
module load macs3/3.0.0
module load deeptools/3.5.1
# ...and so on for all dependencies.

After loading the modules, you can proceed directly to Step 3 above to get the script and run it.