UK10K NEURO ASD BIONED
In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The BioNED (Biomarkers for Childhood onset neuropsychiatric disorders) study has been carrying out detailed phenotypic assessments evaluating children with an autism spectrum disorder. These assessments included ADI-R, ADOS, neuropsychology, EEG etc. There are 56 DNA samples from this study (25 extracted from blood). For further information with regard to this cohort please contact Patrick Bolton (firstname.lastname@example.org).
- Type: Other
- Archiver: EGA European Genome-Phenome Archive
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
|EGAD00001000228||Illumina HiSeq 2000||59|
|EGAD00001000310||Illumina HiSeq 2000||76|
|EGAD00001000434||Illumina HiSeq 2000||77|
The UK10K project identifies rare variants in health and disease.
Nature 526: 2015 82-90
scoreInvHap: Inversion genotyping for genome-wide association studies.
PLoS Genet 15: 2019 e1008203