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 vPECA.zip 85,728.8 kB 1 06-Jun-2019 09:15 YongWang

This page (revision-4) was last changed on 06-Jun-2019 09:20 by YongWang

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We develop a variants interpretation method by Paired Expression and Chromatin Accessibility data to model genome-wide chromatin accessibility profiles for high-altitude hypoxia adaptation in HUVEC, to reveal causal SNPs, active and active selected regulatory elements for a certain gene.
We develop a new method called vPECA (Variants interpretation model by Paired Expression and Chromatin Accessibility data) to model genome-wide chromatin accessibility profiles for high-altitude hypoxia adaptation in HUVEC, to reveal causal SNPs, active and active selected regulatory elements for a certain gene.
vPECA can integrate our measured paired expression and chromatin accessibility data with the available public data, including population genetics data, functional genomics data in ENCODE, and Hi-C data for HUVEC. Our previous work PECA integrates paired expression and chromatin accessibility data across diverse cellular contexts and model the localization to REs of chromatin regulators (CR), the activation of REs due to CRs that are localized to them, and the effect of TFs bound to activated REs on the transcription of target genes (TG) 18. Our innovation here is to extend PECA to interpret genetic variants from population genetics and matched WGS data. vPECA models how positively selected noncoding SNPs affects the RE’s selection status, chromatin accessibility, and activity and further determine the target gene expression. The statistical modelling allows us to systematically identify active REs, active selected REs, and gene regulatory network to interpret variants.
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