Poster #38 - Nicholas Bambach

GATES: a lightweight, automated tool making whole-exome sequencing analysis accessible to scientists with limited computational backgrounds.

Nicholas E. Bambach, MS1, Julio C. Ricarte-Filho, PhD1, Erin R. Reichenberger, PhD2, Aime T. Franco, PhD1,3 1Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, University of Pennsylvania, Philadelphia, PA, United States 2Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, PA, United States 3Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA, United States

Whole-exome sequencing (WES) is a powerful and widely used tool to identify genetic alterations in protein-coding regions of the genome, which account for a disproportionate number of disease-causing variants. WES has applications in both clinical and basic science contexts, including cancer genomics and rare disease studies. Despite its wide utility, analysis of this data is often not possible by scientists without computational expertise. It usually requires access to dedicated bioinformatics engineers and resources, which are not always available. To address these challenges, we developed GATES (GATK Automated Tool for Exome Sequencing), a lightweight package that fully automates and standardizes WES data analysis, making it accessible to scientists with limited computational backgrounds. Utilizing a simple command-line interface, GATES implements GATK Best Practices for both sample preprocessing and variant calling, leverages Ensembl's Variant Effect Predictor (VEP) for variant annotation, and runs end-to-end on a standard laptop. This allows researchers to go from raw FASTQ files to high confidence, annotated variants with just a few simple commands. GATES also automatically downloads and manages all supporting files needed for preprocessing and variant calling so that users only need to input raw FASTQ files, a reference FASTA file, and exon capture regions provided by the library kit manufacturer. All software dependencies are managed through the GATES Conda environment, which is easily created during package installation. GATES supports germline, tumor-only somatic, and paired tumor-normal somatic variant calling, making it applicable to a variety of research areas, including cancer genomics and genetic disorders. We have currently implemented GATES to detect both germline and somatic variants with clinical significance in thyroid tumor samples, as well as identify potential resistance mutations in a thyroid cancer cell line chronically treated with selpercatinib. Built for researchers with limited computational expertise and resources, GATES makes WES analysis accessible, reproducible, and reliable.