Demystifying non-coding GWAS variants: an overview of computational tools and methods

Marijn Schipper, Danielle Posthuma

Research output: Contribution to journalReview articleAcademicpeer-review

8 Citations (Scopus)

Abstract

Genome-wide association studies (GWAS) have found the majority of disease-associated variants to be non-coding. Major efforts into the charting of the non-coding regulatory landscapes have allowed for the development of tools and methods which aim to aid in the identification of causal variants and their mechanism of action. In this review, we give an overview of current tools and methods for the analysis of non-coding GWAS variants in disease. We provide a workflow that allows for the accumulation of in silico evidence to generate novel hypotheses on mechanisms underlying disease and prioritize targets for follow-up study using non-coding GWAS variants. Lastly, we discuss the need for comprehensive benchmarks and novel tools for the analysis of non-coding variants.
Original languageEnglish
Pages (from-to)R73-R83
JournalHuman Molecular Genetics
Volume31
Issue numberR1
DOIs
Publication statusPublished - 15 Oct 2022

Keywords

  • Follow-Up Studies
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study/methods
  • Humans
  • Polymorphism, Single Nucleotide/genetics

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