Results 1 to 10 of about 274,572 (340)
Genome-wide association studies (GWASs) have identified many variants associated with complex traits, but identifying the causal gene(s) is a major challenge.
Edward Mountjoy +2 more
exaly +2 more sources
Osteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting
Hou-Feng Zheng
exaly +2 more sources
Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear.
Eleonora Porcu +2 more
exaly +2 more sources
Analyzing genome-wide association studies with an FDR controlling modification of the Bayesian information criterion [PDF]
The prevailing method of analyzing GWAS data is still to test each marker individually, although from a statistical point of view it is quite obvious that in case of complex traits such single marker tests are not ideal.
Bodenstorfer, Bernhard +2 more
core +21 more sources
Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
Zhihong Zhu, , Han Hu
exaly +2 more sources
The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource
The NHGRI-EBI GWAS Catalog (www.ebi.ac.uk/gwas) is a FAIR knowledgebase providing detailed, structured, standardised and interoperable genome-wide association study (GWAS) data to >200 000 users per year from academic research, healthcare and industry ...
E. Sollis +29 more
semanticscholar +1 more source
Discovery of target genes and pathways at GWAS loci by pooled single-cell CRISPR screens
Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects.
John A. Morris +15 more
semanticscholar +1 more source
The Post-GWAS Era: From Association to Function
Michael D Gallagher +1 more
exaly +2 more sources
OBJECTIVE Depression is a common comorbidity of type 2 diabetes. We assessed the causal relationships and shared genetics between them. RESEARCH DESIGN AND METHODS We applied two-sample, bidirectional Mendelian randomization (MR) to assess causality ...
Jared G. Maina +10 more
semanticscholar +1 more source
Contribution of common and rare variants to bipolar disorder susceptibility in extended pedigrees from population isolates. [PDF]
Current evidence from case/control studies indicates that genetic risk for psychiatric disorders derives primarily from numerous common variants, each with a small phenotypic impact. The literature describing apparent segregation of bipolar disorder (BP)
Aldana, Ileana +37 more
core +3 more sources

