Protocol for using GRPath to identify putative gene regulation paths in complex human diseases
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Published on: October 13, 2023
Xi Xi1, Haochen Li2, Lei Wei1
1MOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China.
Abstract:
Unfolding the "black-box" associations between genotype and phenotype is essential for understanding the molecular mechanisms of complex human diseases. Here, we describe the use of GRPath to uncover putative causal paths (pcPaths) from genetic variants to disease phenotypes. GRPath takes multiple omics data and summary statistics as input and identifies pcPaths that link the putative causal region (pcRegion), putative causal variant (pcVariant), putative causal gene (pcGene), noteworthy cell type, and disease phenotype. For complete details on the use and execution of this protocol, please refer to Xi et al. (2022).1.
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