Literature DB >> 22135417

SNPxGE(2): a database for human SNP-coexpression associations.

Yupeng Wang1, Sandeep J Joseph, Xinyu Liu, Michael Kelley, Romdhane Rekaya.   

Abstract

MOTIVATION: Recently, gene-coexpression relationships have been found to be often conditional and dynamic. Many studies have suggested that single nucleotide polymorphisms (SNPs) have impacts on gene expression variations in human populations.
RESULTS: The SNPxGE(2) database contains the computationally predicted human SNP-coexpression associations, i.e. the differential coexpression between two genes is associated with the genotypes of an SNP. These data were generated from a large-scale association study that was based on the HapMap phase I data, which covered 269 individuals from 4 human populations, 556 873 SNPs and 15 000 gene expression profiles. In order to reduce the computational cost, the SNP-coexpression associations were assessed using gap/substitution models, proven to have a comparable power to logistic regression models. The results, at a false discovery rate (FDR) cutoff of 0.1, consisted of 44 769 and 50 792 SNP-coexpression associations based on single and pooled populations, respectively, and can be queried in the SNPxGE(2) database via either gene symbol or reference SNP ID. For each reported association, a detailed information page is provided. AVAILABILITY: http://lambchop.ads.uga.edu/snpxge2/index.php CONTACT: wyp1125@uga.edu, rrekaya@uga.edu.

Entities:  

Mesh:

Year:  2011        PMID: 22135417     DOI: 10.1093/bioinformatics/btr663

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

1.  xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data.

Authors:  Baishali Bandyopadhyay; Veda Chanda; Yupeng Wang
Journal:  Cancer Inform       Date:  2017-08-28

2.  COXPRESdb: a database of comparative gene coexpression networks of eleven species for mammals.

Authors:  Takeshi Obayashi; Yasunobu Okamura; Satoshi Ito; Shu Tadaka; Ikuko N Motoike; Kengo Kinoshita
Journal:  Nucleic Acids Res       Date:  2012-11-29       Impact factor: 16.971

3.  dcVar: a method for identifying common variants that modulate differential correlation structures in gene expression data.

Authors:  Caleb A Lareau; Bill C White; Courtney G Montgomery; Brett A McKinney
Journal:  Front Genet       Date:  2015-10-19       Impact factor: 4.599

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.