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2017 ; 45
(5
): 2307-2317
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Quantifying deleterious effects of regulatory variants
#MMPMID27980060
Li S
; Alvarez RV
; Sharan R
; Landsman D
; Ovcharenko I
Nucleic Acids Res
2017[Mar]; 45
(5
): 2307-2317
PMID27980060
show ga
The majority of genome-wide association study (GWAS) risk variants reside in
non-coding DNA sequences. Understanding how these sequence modifications lead to
transcriptional alterations and cell-to-cell variability can help unraveling
genotype-phenotype relationships. Here, we describe a computational method,
dubbed CAPE, which calculates the likelihood of a genetic variant deactivating
enhancers by disrupting the binding of transcription factors (TFs) in a given
cellular context. CAPE learns sequence signatures associated with putative
enhancers originating from large-scale sequencing experiments (such as ChIP-seq
or DNase-seq) and models the change in enhancer signature upon a single
nucleotide substitution. CAPE accurately identifies causative cis-regulatory
variation including expression quantitative trait loci (eQTLs) and DNase I
sensitivity quantitative trait loci (dsQTLs) in a tissue-specific manner with
precision superior to several currently available methods. The presented method
can be trained on any tissue-specific dataset of enhancers and known functional
variants and applied to prioritize disease-associated variants in the
corresponding tissue.
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