ICC Pipeline

This pipeline is designed for DNA sequencing analysis, specifically tailored for cardiology research. It leverages Snakemake for workflow management and Conda for environment management.

Table of Contents

• Installation
• Usage
• Workflow Overview
• Rules
  • Quality Control
  • Trimming
  • Alignment
  • Variant Calling
  • Variant Filtering
  • Annotation
• Resource Tracking

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/icc-pipeline.git
   cd icc-pipeline

2. Install Conda environments:

   conda env create -f environment.yml

3. Activate the environment:

   conda activate icc_pipeline

Usage

To run the pipeline, use the cidna.py script with the required arguments:

./cidna.py run workflow/config.yml -i /path/to/input -o /path/to/output -- -c88 --printshellcmds --rerun-incomplete

Workflow Overview

The pipeline consists of several steps, each managed by Snakemake rules. The main steps include:

1. Quality Control: Initial quality checks on raw sequencing data.
2. Trimming: Removing adapters and low-quality bases.
3. Alignment: Aligning reads to the reference genome.
4. Variant Calling: Identifying variants from the aligned reads.
5. Variant Filtering: Filtering the identified variants.
6. Annotation: Annotating the filtered variants.

Rules

Quality Control

• Rule: raw_fastqc
• Description: Runs FastQC on raw sequencing data.
• Input: Raw FASTQ files.
• Output: FastQC reports.

Trimming

• Rule: trimming
• Description: Trims adapters and low-quality bases using Prinseq.
• Input: Raw FASTQ files.
• Output: Trimmed FASTQ files.

Alignment

• Rule: bwa_alignment
• Description: Aligns trimmed reads to the reference genome using BWA.
• Input: Trimmed FASTQ files.
• Output: BAM files.

Variant Calling

• Rule: haplotypecaller
• Description: Calls variants using GATK HaplotypeCaller.
• Input: Realigned BAM files.
• Output: VCF files.

Variant Filtering

• Rule: filter_variants
• Description: Filters variants using GATK VariantFiltration.
• Input: VCF files.
• Output: Filtered VCF files.

Annotation

• Rule: annotate_variants
• Description: Annotates variants using VEP.
• Input: Filtered VCF files.
• Output: Annotated VCF files.

Resource Tracking

The pipeline tracks resource usage, including CPU, memory, and network usage. A detailed report is generated at the end of the pipeline run.

Inhouse vs new pipeline changelog

• Removed IndelRealigner and RealignerTargetCreator because gatk4 HaplotypeCaller realigns the reads on the fly.
• Removed samtools and used sambamba with the same filters as the original command
• Removed gatk CallableLoci and kept gatk DepthOfCoverage. Both are coverage-based and can be addressed in one step with the right configuration. (the below args need to be added though) --omitDepthOutputAtEachBase false
  --includeDeletions true