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 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.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