__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.

* [PECA|http://web.stanford.edu/~zduren/PECA/]


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Category: [Software]