Allele-Specific Expression (ASE) is a measurement of the difference of gene expression between the two alleles of a gene in a heterozygous individual. This difference (also called `allelic imbalance') can be due to many biological processes, including presence of cis-regulatory genetic variants, imprinting, and nonsense-mediated decay.
This track hub shows summary tracks of ASE identified from transcriptome and genotype data collected in 53 tissues by the Genotype-Tissue Expression (GTEx) project, and analyzed by the GTEx Analysis Group (Lappalainen Lab at the New York Genome Center).
The GTEx project was initiated by the NIH as a sample and data resource for studies on the relationship between genetic variation and gene expression in multiple human tissues. The data presented here is from the GTEx midpoint milestone data release (V6, October 2015). For additional information, see the GTEx Analysis hub description.
For detailed analysis of ASE patterns in GTEx, the full ASE data is available via dbGap.
The ASE Density track provides a cross-tissue summary of ASE via a density graph of median allelic imbalance across all tissues in a sliding window.
The ASE Sites track shows all SNPs with evidence of ASE in any tissue. Each site is identified by the SNP ID, or if none assigned, then by chromosomal start position.
The ASE by Tissue track contains a subtrack showing ASE sites for each of the 53 tissues assayed. Sites are colored based on the median ASE for the site across all samples of the tissue; shaded from gray (low) to the GTEx convention tissue color (high) with an intermediate color representing moderate ASE level.
Allelic expression tracks were generated on a per tissue basis. Allelic counts were generated at heterozygous variants called from Illumina OMNI 2.5 Array genotyping with imputation using the GATK ASEReadCounter tool. Only uniquely aligned reads with a base quality of at least 10 at heterozygous sites were used.
The allelic imbalance value per site (ranged between 0 and 0.5) is the median allelic imbalance across individuals with sufficient allelic coverage, calculated as |0.5-REF_COUNT/(REF_COUNT+ALT_COUNT)|. Sites with low mappability (ENCODE 50 bp mappability score less than 1) or that showed mapping bias in simulations (Panousis et al., 2014) were removed.
The cross-tissue density graph was generated by a sliding window algorithm (window size 10 variants, step of 2 variants). Only those variants within 10kb of the first variant in the window are included.
Data and suggestions for track design were provided by the Lappalainen lab at the New York Genome Center, part of the GTEx Analysis Working Group.
For questions about the methods or interpretation of the ASE data presented here, contact Stephane Castel, Lappalainen Lab, NY Genome Center. For questions about this track hub, contact the UCSC Genome Browser mailing list.
Castel SE, Levy-Moonshine A, Mohammadi P, Banks E, Lappalainen T. Tools and best practices for data processing in allelic expression analysis. Genome Biol. 2015 Sep 17;16:195. PMID: 26381377; PMC: PMC4574606