GTEx Consortium

Estimating the causal tissues for complex traits and diseases

This paper estimates the causal tissues for complex traits and diseases by analyzing eQTLs from the GTEx consortium and adapting the RTC score to calculate tissue sharing probabilities.

The impact of structural variation on human gene expression

This study identifies structural variants (SVs) as significant contributors to gene expression, finding they are more frequent causal variants than previously estimated and have larger effect sizes.

Landscape of X chromosome inactivation across human tissues

This paper systematically surveys X chromosome inactivation across human tissues using transcriptomic and genomic data, finding that XCI is generally uniform but shows heterogeneity and identifies new escape genes with sex-biased expression.

Distant regulatory effects of genetic variation in multiple human tissues

The paper identifies trans-eQTLs in multiple human tissues and shows their tissue-specific effects and association with disease.

Local genetic effects on gene expression across 44 human tissues

This study identifies cis-eQTLs across 44 human tissues using GTEx data, showing 88% of genes have cis-eQTLs and demonstrating their utility in understanding complex trait etiology.

The impact of rare variation on gene expression across tissues

The paper identifies rare variants contributing to extreme gene expression changes across tissues and introduces RIVER, a Bayesian method to prioritize functional variants.

Survey of the Heritability and Sparsity of Gene Expression Traits Across Human Tissues

The paper surveys heritability and sparsity of gene expression traits across human tissues, finding local heritability is sparse and current sample sizes limit distal heritability analysis.

PrediXcan: Trait Mapping Using Human Transcriptome Regulation

PrediXcan maps traits to genes by imputing gene expression from GWAS data using reference transcriptomes, identifying disease-associated genes and their mechanisms.

Sharing and specificity of co-expression networks across 35 human tissues

The paper learns tissue-specific gene regulatory networks for 35 human tissues using a transfer learning approach, showing that tissue-specific transcription factors are hubs and genes with tissue-specific functions are at network peripheries.

Assessing allele specific expression across multiple tissues from RNA-seq read data

The paper introduces a statistical method to analyze allele-specific expression across tissues and classifies variants based on their regulatory impact using RNA-seq data.