BTS: scalable Bayesian Tissue Score for prioritizing GWAS variants and their functional contexts across omics data.

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Title: BTS: scalable Bayesian Tissue Score for prioritizing GWAS variants and their functional contexts across omics data.
Authors: Kuksa PP; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Ionita M; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Carter L; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Cifello J; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Clark K; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Valladares O; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Leung YY; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA., Wang LS; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Source: BioRxiv : the preprint server for biology [bioRxiv] 2025 Feb 05. Date of Electronic Publication: 2025 Feb 05.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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PubType: Academic Journal
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  Data: BTS: scalable Bayesian Tissue Score for prioritizing GWAS variants and their functional contexts across omics data.
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  Data: <searchLink fieldCode="AU" term="%22Kuksa+PP%22">Kuksa PP</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Ionita+M%22">Ionita M</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Carter+L%22">Carter L</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Cifello+J%22">Cifello J</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Clark+K%22">Clark K</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Valladares+O%22">Valladares O</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Leung+YY%22">Leung YY</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.<br /><searchLink fieldCode="AU" term="%22Wang+LS%22">Wang LS</searchLink>; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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  Data: <searchLink fieldCode="JN" term="%22101680187%22">BioRxiv : the preprint server for biology</searchLink> [bioRxiv] 2025 Feb 05. <i>Date of Electronic Publication: </i>2025 Feb 05.
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  Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101680187 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2692-8205 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2226928205%22">26928205 </searchLink><i>NLM ISO Abbreviation: </i>bioRxiv <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1101/2024.10.30.621077
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              Text: 2025 Feb 05
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