Beyond GWASs: illuminating the dark road from association to function.

By S. Edwards, J. Beesley, J. French, Alison M. Dunning. American Journal of Human Genetics, 2013

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View Paper: https://www.semanticscholar.org/paper/5e34bdd13ef42e295829d41da2d82d0a747e4b53

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Citations in the corpus

Identifying Causal Variants at Loci with Multiple Signals of Association (2014, background): “CAVIAR can easily take into account data on putative function of variants either from functional genomic data (Bernstein et al. 2012) or from eQTL data that have been recently shown to help facilitate fine-mapping studies (Hoffman et al. 2012; Edwards et al. 2013).”
Functional mapping and annotation of genetic associations with FUMA (2017, methodology): “As a variety of bioinformatics tools have been developed to obtain insights in GWAS results 23 – 25 , we compared the list of features available in FUMA with the features available in other tools, and describe these further below (Table 1).”
Rare-variant association analysis: study designs and statistical tests. (2014, background): “115,116 Such studies are often the logical next step once clear statistical evidence of association has been established and localized.”
A Whole-Genome Analysis Framework for Effective Identification of Pathogenic Regulatory Variants in Mendelian Disease. (2016, background): “…studies (GWASs) have identiﬁed more than 10,000 strong associations (p < 10 (cid:1) 5 ) between diseases or traits and SNVs, most of which are located in non-coding sequences; 4 however, in Mendelian disease, mutations in non-coding regions represent a tiny minority of all those published to date.”
The Post-GWAS Era: From Association to Function. (2018, methodology): “, it can be extremely difficult to know a priori what the target gene(s) of the CRE harboring the variant might be.(10) ‘‘One-versusall’’ approaches—in which a specific genomic region is captured or selectively amplified in conjunction with all interacting regions—are well-suited to identify the tar”
Application of t-SNE to Human Genetic Data (2017, background): “It may also sit between genes which probably change a binding motif of a transcription factor which leads to a change of the transcription (expression) level [8].”
Analysis of predicted loss-of-function variants in UK Biobank identifies variants protective for disease (2018, methodology): “Studies included in the MIGen consortium were: (1) the Italian Atherosclerosis Thrombosis and Vascular Biology (ATVB) study (dbGaP Study Accession phs000814.”