The IGVF catalog—from genetic variation to function

作者：Daofeng Li, Shane Liu, Pedro Assis, Mingjie Li, Shengcheng Dong, Ian Whaling, Otto Jolanki, Meenakshi S. Kagda, Wenjin Zhang, Juan F Macias-Velasco, Tianjie Liu, Sarah Cody, Lucinda Antonacci-Fulton, Yuanhao Huang, Jie Liu, Michael T. Montgomery, Daniel Zeiberg, Shantanu Jain, Vikas Pejaver, Timothy Bergquist, Yile Chen, Predrag Radivojac, Charles A. Gersbach, Rintsen N. Sherpa, Christopher P. Castro, Alan P. Boyle, Lea M. Starita, Douglas M. Fowler, Nadav Ahituv, Kushal K. Dey, William H. Majoros, Timothy E. Reddy, Mark Craven, Riya Sinha, Yuriy Sverchkov, Xiangmeng Cai, Mpathi Nzima, Michael A. Calderwood, Joel Rozowsky, Mark Gerstein, Jian Ma, Feng Yue, J. Michael Cherry, Michael I. Love, J Engreitz, Benjamin C. Hitz, Ting Wang · 发表于：Nucleic Acids Research · 年份：2025 · DOI：10.1093/nar/gkaf1341 · 被引用次数：3 · 研究领域：Single-cell and spatial transcriptomics、Genomics and Rare Diseases、Genetic Associations and Epidemiology

Genomic variation between individuals is essential for understanding how differences in the genome sequence affect molecular and cellular processes. The Impact of Genomic Variation on Function (IGVF) Consortium aims to uncover the relationships among genomic variation, genome function, and phenotypes by combining experimental techniques, such as single-cell mapping and genomic perturbation assays, with computational approaches such as machine learning-based predictive modeling. The IGVF Data and Administrative Coordinating Centers collect, analyze, and disseminate data and results from across the consortium through an open-source platform called the IGVF Catalog. This resource includes, but is not limited to, data on the effects of coding variants on protein abundance and function, noncoding variants on enhancer activity (measured by MPRA or predicted computationally), and associations between variants and quantitative traits. All data are organized within a graph database comprising over 50 types of data collections with nearly 3 billion nodes and over 7.5 billion edges. The Catalog offers public API endpoints (https://api.catalogkg.igvf.org/) and a user-friendly interface for exploring, querying, and visualizing the data at https://catalog.igvf.org. We expect that this open-access platform will support the broader scientific community to advance our understanding of how genomic variation influences biology and disease.