ILIAD: a suite of automated Snakemake workflows for processing genomic data for downstream applications

Area of Science:

• Bioinformatics
• Genomic Data Analysis
• Computational Biology

Background:

• Processing raw genomic data for downstream applications is time-consuming and resource-intensive.
• Disjointed use of bioinformatics tools leads to increased difficulty and error rates.
• Automated and reproducible workflows are crucial for efficient genomic data processing.

Purpose of the Study:

• To develop a suite of automated genomic data workflows for seamless data processing.
• To provide a stable, reproducible, and user-friendly solution for biologists.
• To overcome computational and storage challenges in genomic data analysis.

Main Methods:

• The Iliad suite utilizes the Snakemake framework with Singularity and Docker containers.
• It supports various raw data types (FASTQ, CRAM, IDAT) and integrates tools like BWA, Samtools, and BCFtools.
• Workflows are configurable via a single file and compatible across multiple platforms.

Main Results:

• Iliad automates the transition from raw genomic data to quality-controlled variant call format (VCF) files.
• It optimizes time and resource management, comparable to existing workflows.
• Temporary intermediate files are used to manage storage footprint challenges.

Conclusions:

• Iliad generates analysis-ready VCF files from common datatypes with a single command.
• The suite is portable, scalable, robust, and repeatable, simplifying big data management for biologists.
• It facilitates downstream applications such as imputation, genome-wide association studies, and population genetics.