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Empowering Immunogenetic Analysis with Biofilter 3.0 via Enhanced Annotation and Filtering Capabilit

Van Q. Truong, Xueqiong Li, Scott Dudek, Rasika Venkatesh, E. John Wherry, Marylyn D. Ritchie


Poster # 22


Autoimmune diseases are a growing global health concern, affecting approximately 4.5% of people worldwide. In addition, 25% of affected individuals suffer from multiple autoimmune disorders. While hundreds of genetic variants have been identified for the most common autoimmune diseases, the small effect sizes and limited explanatory power underscore the need for an integrative knowledge-driven approach. The body of knowledge for genetic and immunological information is vast and oftentimes overwhelming. We discuss how incorporating immune-relevant information can empower the discovery and interpretation of combinations of genetic variations based on prior immunological knowledge. In this work, we present Biofilter 3.0 which contains enhanced annotation and filtering capabilities for empowering immunogenetic analyses. Previous versions of Biofilter provided a convenient single interface for accessing multiple publicly available human biological databases stored within the supporting knowledgebase of the Library of Knowledge Integration (LOKI). We integrated additional public databases of autoimmune and immune-mediated information into LOKI to bolster existing information on genomic locations of SNPs, genes, ontological categories, and interaction pairs. Furthermore, we expanded the functionality of Biofilter to make it possible to leverage this prior knowledge in analyses. This approach yields a collection of functions which enable researchers to efficiently annotate, subset, and filter thousands of SNPs, genes, proteins, and genomic locations based on immunological criteria, including relevant immune terms, pathways, and/or diseases.

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