Sequencing Facility Fastq-QC pipeline: No pipe

No Pipe is an abbreviated pipeline that will run Fastqc, Fastq screen and generate MultiQC report.

Quality Control (QC):

FastQC: Perform initial quality checks on raw sequencing data to assess sequence quality, GC content, over-representation of sequences, etc.

Fastq Screen: Screens sequencing data against a database of known contaminants, such as adapter sequences, PhiX control, and various other sources of contamination. It helps to identify and quantify the presence of these contaminants in the sequencing data.

MultiQC : Generates an interactive HTML report that provides a concise summary of the results

Usage

Step 1: Obtain a copy of this workflow

Clone the Repository: Clone the new repository to your local machine, choosing the directory where you want to perform data analysis. Instructions for cloning can be found here.

Step 2: Configure workflow

Configure the workflow according to your needs via editing the config.yaml file in the config/ folder. For test purpose: use mock data located in test folder.

Step 3: Load the snakemake version 8 or above

module load snakemake/8.4.8

Step 4: Create a conda environment

$NAME=my_environment_name

conda create -n $NAME

Step 5: Execute the Workflow

Activate the Conda Environment:

conda activate $NAME

Install mamba

conda install -c conda-forge mamba

Perform a dry-run to validate your setup:

snakemake --use-conda -np

Local Execution: Execute the workflow on your local machine using $N cores:

snakemake --use-conda --cores $N

Here, $N represents the number of cores you wish to allocate for the workflow.

Step 6: Investigate results

After successful execution, HTML report with QC results will be generated.

conda deactivate

Contact

[email protected]