Fastq2vcf: a concise and transparent pipeline for whole-exome sequencing data analyses

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Whole-exome sequencing (WES) is a widely adopted next-generation sequencing technique.
• Centralized databases enable data reanalysis, underscoring the need for accessible and reproducible analysis tools.
• Varied expertise levels in laboratories necessitate software to simplify complex genomic data analysis.

Purpose of the Study:

• To develop an automated software pipeline for whole-exome sequencing (WES) data analysis.
• To enhance the reproducibility and efficiency of genomic variant calling.
• To lower the technical expertise required for WES data interpretation.

Main Methods:

• Developed fastq2vcf, a versatile pipeline integrating multiple genomic variant callers.
• Automated the genomic variant calling process from raw sequencing data (FASTQ) to variant call files (VCF).
• Enabled customization and extension of the analysis workflow for diverse research needs.

Main Results:

• fastq2vcf automates genomic variant calling using multiple callers, improving flexibility and efficiency.
• The pipeline outputs annotated variant call sets and a consensus set derived from multiple callers.
• The software facilitates easy job submission and tracking in various computing environments.

Conclusions:

• fastq2vcf simplifies WES data analysis, making it reproducible across different laboratories.
• The tool provides users with full control over the analysis procedure.
• This pipeline lowers the barrier to entry for complex genomic data analysis.