Thomas Cheng Li, Hufeng Zhou, Vineet Verma, Xiangru Tang, Yanjun Shao, Eric Van Buren, Zhiping Weng, Mark Gerstein, Benjamin Neale, Shamil R Sunyaev, Xihong Lin
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引用次数: 0
Abstract
Motivation: Functional Annotation of genomic Variants Online Resources (FAVOR) offers multi-faceted, whole genome variant functional annotations, which is essential for Whole Genome and Exome Sequencing (WGS/WES) analysis and the functional prioritization of disease-associated variants. A versatile chatbot designed to facilitate informative interpretation and interactive, user-centric summary of the whole genome variant functional annotation data in the FAVOR database is needed.
Results: We have developed FAVOR-GPT, a generative natural language interface powered by integrating large language models (LLMs) and FAVOR. It is developed based on the Retrieval Augmented Generation (RAG) approach, and complements the original FAVOR portal, enhancing usability for users, especially those without specialized expertise. FAVOR-GPT simplifies raw annotations by providing interpretable explanations and result summaries in response to the user's prompt. It shows high accuracy when cross-referencing with the FAVOR database, underscoring the robustness of the retrieval framework.
Availability and implementation: Researchers can access FAVOR-GPT at FAVOR's main website (https://favor.genohub.org).
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