KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease
Boulogne F, Claus L, Wiersma H, Oelen R, Schukking F, de Klein N, Li S, Westra H, van der Zwaag B, van Reekum F, Sierks D, Schönauer R, Li Z, Bijlsma E, Bos W, Halbritter J, Knoers N, Besse W, Deelen P, Franke L, van Eerde A. KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease. European Journal Of Human Genetics 2023, 31: 1300-1308. PMID: 36807342, PMCID: PMC10620423, DOI: 10.1038/s41431-023-01296-x.Peer-Reviewed Original ResearchMeSH KeywordsGene ExpressionHumansKidneyKidney DiseasesKidney Diseases, CysticLiver DiseasesPhenotypeConceptsCo-expression networkTissue-specific expressionCandidate genesGene functionPhenotypic consequences of genetic variationPathogenic variantsConsequences of genetic variationInterpretation of genetic variantsGenetic causeRare variantsGene-phenotype associationsHereditary kidney diseaseExome sequencing dataDisease-associated genesGene expression dataPlausible candidate genesCandidate gene prioritizationKidney disease phenotypesUnbiased mannerCystic kidneysNovel genesGenetic variationPhenotypic consequencesGene prioritizationSequence data