Principles and methods of in-silico prioritization of non-coding regulatory variants.
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Abstract | Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research. |
Year of Publication | 2018
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Journal | Hum Genet
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Volume | 137
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Issue | 1
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Pages | 15-30
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Date Published | 2018 Jan
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ISSN | 1432-1203
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DOI | 10.1007/s00439-017-1861-0
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PubMed ID | 29288389
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PubMed Central ID | PMC5892192
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Grant list | R00 MH101367 / MH / NIMH NIH HHS / United States
U01 MH111660 / MH / NIMH NIH HHS / United States
R00MH101367 / National Institute of Mental Health
U01MH111660 / National Institute of Mental Health
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