Demystifying non-coding GWAS variants:an overview of computational tools and methods
| Autor: | Marijn Schipper, Danielle Posthuma |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Genetics
Genome-Wide Association Study/methods Humans Genetic Predisposition to Disease General Medicine Polymorphism Polymorphism Single Nucleotide/genetics Molecular Biology Polymorphism Single Nucleotide Single Nucleotide/genetics Genetics (clinical) Genome-Wide Association Study Follow-Up Studies |
| Zdroj: | Schipper, M & Posthuma, D 2022, ' Demystifying non-coding GWAS variants : an overview of computational tools and methods ', Human molecular genetics, vol. 31, no. R1, pp. R73-R83 . https://doi.org/10.1093/hmg/ddac198 Schipper, M & Posthuma, D 2022, ' Demystifying non-coding GWAS variants : an overview of computational tools and methods ', Human Molecular Genetics, vol. 31, no. R1, pp. R73-R83 . https://doi.org/10.1093/hmg/ddac198 |
| DOI: | 10.1093/hmg/ddac198 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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