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Master regulator activity QTL protocol to implicate regulatory pathways potentially mediating GWAS signals using eQTL data
Here, we present a protocol to identify transcriptional regulators potentially mediating downstream biological effects of germline variants associated with complex traits of interest, which enables functional hypothesis generation independent of colocalizing expression quantitative trait loci (eQTLs...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10285694/ https://www.ncbi.nlm.nih.gov/pubmed/37330907 http://dx.doi.org/10.1016/j.xpro.2023.102362 |
Sumario: | Here, we present a protocol to identify transcriptional regulators potentially mediating downstream biological effects of germline variants associated with complex traits of interest, which enables functional hypothesis generation independent of colocalizing expression quantitative trait loci (eQTLs). We describe steps for tissue-/cell-type-specific co-expression network modeling, expression regulator activity inference, and identification of representative phenotypic master regulators. Finally, we detail activity QTL and eQTL analyses. This protocol requires genotype, expression, and relevant covariables and phenotype data from existing eQTL datasets. For complete details on the use and execution of this protocol, please refer to Hoskins et al.(1) |
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