ASE (Allele-Specific Expression mapping), a statistical framework that increases the computational power of eQTL with an alternative and complementary approach based on analyzing allele specific expression. The principal behind the ASE mapping approach is that if an individual's phenotype heterozygote for a regulatory variant, then the two copies of the gene will show different level of expression (also known as allelic expression imbalance, AEI). Analysis of ASE is advantageous over analyzing total expression levels because the two alleles express at the same cellular environment, providing an internal control for each other. Consequently, trans-acting environmental and genetic factors that increase variation between samples are minimized to similar eQTLs studies, the analysis of ASE is influenced by local LD structure and by amount of allelic heterogeneity. However, the relationship between LD and variant identification has a different flavor utilizing ASE compared to eQTL studies. Thus ASE provides a complimentary approach to identify variants affecting expression compared to traditional eQTL studies.

ASE was created by Jennifer Zou

Download ASE


  • v1.0.0 (2016-09-22) Preliminary version of ASE was deployed


Coming soon.


Eun Yong Kang, Lisa J. Martin, Serghei Mangul, Warin Isvilanonda, Jennifer Zou, Eyal Ben-David, Buhm Han, Aldons J. Lusis, Sagiv Shifman, and Eleazar Eskin. Discovering SNPs Regulating Human Gene Expression Using Allele Specific Expression from RNA-Seq data. Genetics, in press (2016)


For specific questions or bug report about ASE software, please email Jennifer Zou (jzou1115 [AT]