Scalable and efficient DNA sequencing analysis on different compute infrastructures aiding variant discovery.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• DNA variation analysis is crucial for biomedicine, especially in comparing normal and tumor samples.
• Large-scale sequencing efforts generate thousands of samples, necessitating scalable and automated data processing workflows.

Purpose of the Study:

• To present nf-core/sarek 3, a rewritten, comprehensive variant calling and annotation pipeline.
• To enhance scalability, portability, and automation for germline and somatic DNA variation analysis.

Main Methods:

• Full rewrite of the original nf-core/sarek pipeline.
• Implementation of the CRAM format for reduced storage requirements.
• Increased intra-sample parallelization to decrease runtime.

Main Results:

• Significant reduction in storage needs and processing time.
• Achieved a 70% cost reduction in commercial cloud environments.
• Enables large-scale, cross-platform genomic data analysis with lower costs and environmental impact.

Conclusions:

• nf-core/sarek 3 offers a cost-effective and efficient solution for DNA variation analysis.
• The pipeline supports any genome with a known reference, facilitating broad applicability.
• The optimized workflow supports sustainable and large-scale genomic research.