vPECA: variants interpretation method by Paired Expression and Chromatin Accessibility data
- Version 1.0
- Last updated: June 6, 2019
Reference#
- Jingxue Xin, Hui Zhang, Yaoxi He, Zhana Duren, Chaoying Cui, Lang Chen, Xin Luo, Dong-Sheng Yan, Chaoyu Zhang, Xiang Zhu, Qiuyue Yuan, Xuebing Qi, Ouzhuluobu, Wing Hung Wong, Yong Wang, Bing Su. Chromatin accessibility landscape and regulatory network of high-altitude hypoxia adaptation. (In submission).
Method#
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.Procedure#
Useful Resource:#
Download 25 bio-sample matched RNA-seq and DNase-seq data from mouse ENCODE project.
Download regulatoryElement-targetGene association.
Download PECA predicted whole network and context specific network for 25 tissues or cell type.
Using PECA Tools:#
PECA-TNet: Matlab tool for context specific network
Input: paired expression of genes (Exp) and chromatin accessibility of regulatory elements (Opn) on your interested cellular context.
Output: context specific network (TissueSpecificNet).
Usage: TissueSpecificNet=PECATool1(Exp,Opn,GeneName,ElementName);
Where GeneName and ElementName are name of gene and regulatory elements.
PECA-Anno: Matlab tool for genomic region annotation by network
Input: Bed file of the genomic region you interested (region.bed’).
Output: annotation network of your region (RegionNet).
Usage: RegionNet=PECATool2(‘region.bed’);
Software#
This is a beta version of the program for preliminary testing. The program is still under development.
Category: Software