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FAVOR-GPT: a generative natural language interface to whole genome variant functional annotations

Li, Thomas Cheng
Zhou, Hufeng
Verma, Vineet
Tang, Xiangru
Shao, Yanjun
Van Buren, Eric
Weng, Zhiping
Gerstein, Mark
Neale, Benjamin
Sunyaev, Shamil R
... show 1 more
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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).

Source

Li TC, Zhou H, Verma V, Tang X, Shao Y, Van Buren E, Weng Z, Gerstein M, Neale B, Sunyaev SR, Lin X. FAVOR-GPT: a generative natural language interface to whole genome variant functional annotations. Bioinform Adv. 2024 Sep 28;4(1):vbae143. doi: 10.1093/bioadv/vbae143. PMID: 39387060; PMCID: PMC11461909.

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DOI
10.1093/bioadv/vbae143
PubMed ID
39387060
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© The Author(s) 2024. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.