The majority of GWAS (Genome-Wide Association Study) identified common genetic variants map to regulatory regions of gene, and are likely to influence disease risk by affecting gene expression. One of the most important challenges is to experimentally fine-map causal regulatory variants that typically lie in credible intervals of 100 or more variants. Another large proportion of genetic variants, rare variants, are expected to have large effects causing disease in individual, but are not detectable in GWAS. Herein, I provide both experimental and computational approaches for fine-mapping common and rare genetic variants accounting for medium and large effect on population or individual. First, I describe a single cell clone-based strategy f...
Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify comm...
Rare and common regulatory variation in population-scale sequenced human genomes MONTGOMERY, Stephen...
Background: Genome wide association studies (GWAS) are a population-scale approach ...
The majority of genome-wide association study (GWAS)-identified SNPs are located in noncoding region...
The majority of genetic variants affecting complex traits map to regulatory regions of genes, and ty...
The advent of genotyping and sequencing technologies has enabled human genetics to discover numerous...
Evidence from Genome Wide Association Studies (GWAS) has provided us with insights into human phenot...
AbstractGenome-wide association studies (GWASs) have shown a large number of genetic variants to be ...
Interpreting human regulatory variants in the noncoding genomic region is critical to understand the...
Genome wide association studies (GWA) have had tremendous success in identifying genetic variants as...
Over the past 15 years, genome-wide association studies (GWASs) have enabled the systematic identifi...
This dissertation aims at investigating the association between genotypes and phenotypes in human. B...
The recent advances in genomic technologies, have made it possible to collect large-scale informatio...
Genome-wide association studies (GWAS) have greatly improved our understanding of the genetic basis ...
Thesis advisor: Gabor T. MarthPartitioning an individual's phenotype into genetic and environmental ...
Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify comm...
Rare and common regulatory variation in population-scale sequenced human genomes MONTGOMERY, Stephen...
Background: Genome wide association studies (GWAS) are a population-scale approach ...
The majority of genome-wide association study (GWAS)-identified SNPs are located in noncoding region...
The majority of genetic variants affecting complex traits map to regulatory regions of genes, and ty...
The advent of genotyping and sequencing technologies has enabled human genetics to discover numerous...
Evidence from Genome Wide Association Studies (GWAS) has provided us with insights into human phenot...
AbstractGenome-wide association studies (GWASs) have shown a large number of genetic variants to be ...
Interpreting human regulatory variants in the noncoding genomic region is critical to understand the...
Genome wide association studies (GWA) have had tremendous success in identifying genetic variants as...
Over the past 15 years, genome-wide association studies (GWASs) have enabled the systematic identifi...
This dissertation aims at investigating the association between genotypes and phenotypes in human. B...
The recent advances in genomic technologies, have made it possible to collect large-scale informatio...
Genome-wide association studies (GWAS) have greatly improved our understanding of the genetic basis ...
Thesis advisor: Gabor T. MarthPartitioning an individual's phenotype into genetic and environmental ...
Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify comm...
Rare and common regulatory variation in population-scale sequenced human genomes MONTGOMERY, Stephen...
Background: Genome wide association studies (GWAS) are a population-scale approach ...