Type 1 Diabetes Risk in African-Ancestry Participants and Utility of an Ancestry-Specific Genetic Risk Score.
Onengut-Gumuscu S, et al.
Diabetes Care. 2019 Mar;42(3):406-415. doi: 10.2337/dc18-1727.
PMID:30659077
Tutorial for the Genome-Wide APOL1 Correlations View
We calculated Spearman correlations between APOL1 expression and normalized expression for each gene in high-risk (HR), low-risk (LR), and normal samples. To compare HR to LR correlations, we transformed the correlations using the Fisher Z-transformation.
Summary statistics are available for download from the GWAS Catalog.
GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits.
Pazoki R, et al.
Nat Commun. 2019 Aug 13;10(1):3653. doi: 10.1038/s41467-019-11451-y.
PMID:31409800
Summary statistics are available for download at the deCODE Genetics website.
Eighty-eight variants highlight the role of T cell regulation and airway remodeling in asthma pathogenesis.
Olafsdottir TA, et al.
Nat Commun. 2020 Jan 20;11(1):393. doi: 10.1038/s41467-019-14144-8.
PMID:31959851
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the GIANT 2018 Body Fat Distribution exome chip analysis dataset.
This dataset is a subset of the ExTexT2D exome chip analysis dataset.
Note that the samples in the GoT2D exome chip analysis and FUSION exome chip analysis datasets are a subset of those included in the ExTexT2D exome chip analysis dataset. Cases in the EXTEND GWAS dataset are included in the ExTexT2D exome chip analysis dataset.