Principles and methods of in-silico prioritization of non-coding regulatory variants

被引:0
|
作者
Phil H. Lee
Christian Lee
Xihao Li
Brian Wee
Tushar Dwivedi
Mark Daly
机构
[1] Massachusetts General Hospital and Harvard Medical School,Center for Genomic Medicine
[2] Harvard T.H. Chan School of Public Health,Quantitative Genomics Program
[3] Harvard University,Department of Life Sciences
[4] Harvard T.H. Chan School of Public Health,Department of Biostatistics
[5] Harvard University,John A. Paulson School of Engineering and Applied Sciences
[6] Broad Institute of MIT and Harvard,Program in Medical and Population Genetics
来源
Human Genetics | 2018年 / 137卷
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摘要
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.
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页码:15 / 30
页数:15
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