Browsing by Author "Nizomov, Javlon"

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    MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants
    (Oxford University Press, 2024) Jin, Weijia; Xia, Yi; Nizomov, Javlon; Liu, Yunlong; Li, Zhigang; Lu, Qing; Chen, Li; Medical and Molecular Genetics, School of Medicine
    Summary: Massively parallel reporter assay (MPRA) is an important technology for evaluating the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs, and genomic features, totaling 242 818 variants tested more than 30 cell lines and 30 human diseases or traits. MPRAVarDB enables users to query MPRA variants by genomic region, disease and cell line, or any combination of these parameters. Notably, MPRAVarDB offers a suite of pretrained machine-learning models tailored to the specific disease and cell line, facilitating the prediction of regulatory variants. The user-friendly interface allows users to receive query and prediction results with just a few clicks. Availability and implementation: https://mpravardb.rc.ufl.edu.
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    MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants
    (bioRxiv, 2024-04-03) Nizomov, Javlon; Jin, Weijia; Xia, Yi; Liu, Yunlong; Li, Zhigang; Chen, Li; Medical and Molecular Genetics, School of Medicine
    Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits. MPRAVarDB empowers the query of MPRA variants by genomic region, disease and cell line or by any combination of these query terms. Notably, MPRAVarDB offers a suite of pretrained machine learning models tailored to the specific disease and cell line, facilitating the genome-wide prediction of regulatory variants. MPRAVarDB is friendly to use, and users only need a few clicks to receive query and prediction results.