AdaGenes: A streaming processor for high-throughput annotation and filtering of sequence variant data
MotivationThe amount of sequencing data resulting from whole exome and whole genome sequencing (WES / WGS) presents challenges for annotation, filtering, and analysis. These challenges are exacerbated by the need for efficient and scalable tools that can handle the vast amounts of data generated by modern sequencing technologies. ResultsWe introduce the Adaptive Genes processor (AdaGenes), a sequence variant streaming processor designed to efficiently annotate, filter, LiftOver and transform large-scale VCF files. AdaGenes provides a unified solution for researchers to streamline VCF processing workflows and address common challenges in genomic data processing, e.g. to filter out non-relevant variants to focus on further processing of the relevant positions. Ada-Genes integrates genomic, transcript and protein data annotations, while maintaining scalability and performance for high-throughput workflows. Leveraging a streaming architecture, AdaGenes processes variant data incrementally, enabling high-performance on large files due to low memory consumption. The interactive front end provides the user with the ability to dynamically filter variants based on user-defined criteria. It allows researchers and clinicians to efficiently analyze large genomic datasets, facilitating variant interpretation in diverse genomics applications, such as population studies, clinical diagnostics, and precision medicine. AdaGenes is able to parse and convert multiple file formats while preserving metadata, and provides a report of the changes made to the variant file. Availability and implementationA public instance of AdaGenes is available at https://mtb.bioinf.med.uni-goettingen.de/adagenes. The source code is available at https://gitlab.gwdg.de/MedBioinf/mtb/adagenes.