Asset Details
Do you wish to reserve the book?
GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals
Do you wish to request the book?
GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals
2019
Overview
Loci discovered by genome-wide association studies predominantly map outside protein-coding genes. The interpretation of the functional consequences of non-coding variants can be greatly enhanced by catalogs of regulatory genomic regions in cell lines and primary tissues. However, robust and readily applicable methods are still lacking by which to systematically evaluate the contribution of these regions to genetic variation implicated in diseases or quantitative traits. Here we propose a novel approach that leverages genome-wide association studies’ findings with regulatory or functional annotations to classify features relevant to a phenotype of interest. Within our framework, we account for major sources of confounding not offered by current methods. We further assess enrichment of genome-wide association studies for 19 traits within Encyclopedia of DNA Elements- and Roadmap-derived regulatory regions. We characterize unique enrichment patterns for traits and annotations driving novel biological insights. The method is implemented in standalone software and an R package, to facilitate its application by the research community.
GARFIELD is a new approach that classifies genomic features related to phenotypes on the basis of integrating GWAS signals with functional annotations. GARFIELD is used to characterize enrichment patterns for 29 traits integrated with ENCODE and Roadmap Epigenomics annotations.
Publisher
Nature Publishing Group US,Nature Publishing Group
Subject
/ 45/43
/ Animal Genetics and Genomics
/ Biomedical and Life Sciences
/ Diabetes
/ Disease
/ DNA
/ Genes
/ Genome-wide association studies
/ Genome-Wide Association Study - methods
/ Genomes
/ Genomics
/ Humans
/ Methods
/ Molecular Sequence Annotation - methods
/ Polymorphism, Single Nucleotide - genetics
/ Proteins
/ Quantitative Trait Loci - genetics
/ Regulatory Sequences, Nucleic Acid - genetics
/ Software
