Sort   by:  
 Page size 
Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effectiv...
WTCCC2 samples from 1958 British Birth Cohort
WTCCC2 samples from Type 2 Diabetes Cohort
WTCCC2 samples from Hypertension Cohort
WTCCC2 samples from Coronary Artery Disease Cohort
The development of whole genome association studies from the general population has lead to the robust identification of several loci involved in different common human diseases. Interestingly, most of the strongest signals of association observed in these studies arise from non-coding regions, rais...
ORGANISM(S): Homo sapiens 
The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g....
This data set includes the following summary level data file used for the imputation data: imputation.sv.assoc.txt: results from single variant association analysis in imputed samples
This data set includes the following summary level data files used for the 13k analysis of T2D-GENES data: wes.variants.list: list of variants to keep for any analysis of the exomes data wes.assoc.samples.list: list of samples to keep for association analysis wes.assoc.variants.list: list of variant...
This data set includes the following summary level data files used for the GoT2D WGS analysis: wgs.assoc.samples.list: list of samples to keep for association analysis wgs.assoc.variants.list: list of variants to keep for association analysis wgs.sv.assoc.txt: single variant association results
Sort   by:  
 Page size