Tutorial for the Differential Co-expression View
Differential co-expressed gene modules were built using methods outlined by DiffCoEx. The network adjacency matrix is derived from differences in gene pair Spearman correlations between high-risk (HR) and low-risk (LR) groups. 1,273 genes were clustered into four modules: "Brown," "Purple," "Pink," "Green".
This dataset represents associations on chromosome X in the female subset of the 70KforT2D GWAS dataset.
The 70KforT2D GWAS dataset includes cohorts that are also included in the DIAGRAM Transethnic meta-analysis dataset.
All samples except the non-European GERA samples are included in the "DIAMANTE (European) T2D GWAS" dataset.
This dataset represents the South Asian subset of the AMP T2D-GENES exome sequence analysis dataset.
The 13k exome sequence analysis dataset is a subset of the AMP T2D-GENES exome sequence analysis dataset.
This dataset represents the Hispanic subset of the AMP T2D-GENES exome sequence analysis dataset.
The 13k exome sequence analysis dataset is a subset of the AMP T2D-GENES exome sequence analysis dataset.
This dataset represents the European subset of the AMP T2D-GENES exome sequence analysis dataset.
The 13k exome sequence analysis dataset is a subset of the AMP T2D-GENES exome sequence analysis dataset.
This dataset represents the East Asian subset of the AMP T2D-GENES exome sequence analysis dataset.
The 13k exome sequence analysis dataset is a subset of the AMP T2D-GENES exome sequence analysis dataset.
This dataset represents the African American subset of the AMP T2D-GENES exome sequence analysis dataset.
The 13k exome sequence analysis dataset is a subset of the AMP T2D-GENES exome sequence analysis dataset.
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