GARFIELD classifies disease-relevant genomic features through integration of functional annotations with association signals

Valentina Lotchkova, Graham R S Ritchie, Matthias Geihs, Sandro Morganella, Josine Min, Klaudia Walter, Nicholas Timpson, Ian Dunham, Ewan Birney, Nicole Soranzo*, UK10K Consortium

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

43 Citations (Scopus)
411 Downloads (Pure)

Abstract

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.

Original languageEnglish
Pages (from-to)343-353
Number of pages11
JournalNature Genetics
Volume51
Issue number2
Early online date28 Jan 2019
DOIs
Publication statusPublished - Feb 2019

Structured keywords

  • ICEP

Keywords

  • Disease/genetics
  • Genome/genetics
  • Genome-Wide Association Study/methods
  • Genomics/methods
  • Humans
  • Molecular Sequence Annotation/methods
  • Phenotype
  • Polymorphism, Single Nucleotide/genetics
  • Quantitative Trait Loci/genetics
  • Regulatory Sequences, Nucleic Acid/genetics
  • Software

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