A Unified Quantile Framework for Transcriptome-Wide Association Analysis

Methodology

Software

We developed software tools based on R: QTWAS for training gene expression model on based on GTEx data. Please see the Github page for more details.

Models

We provide pre-trained QTWAS models per gene for 49 tissues in GTEx v8. R scores for evaluating imputation accuracy are also provided for each model.

  • Download all the QTWAS models here. In each database file, we provide the information for:
    • estimated beta at selected SNPs, indexed by rsid and gene ensemble ID. interval represents the quantile region of gene expression, i.e., .
    • covariance matrix of SNPs in the imputation models, indexed by rsid and gene ensemble ID.

    Code to extract the information:

    driver <- dbDriver('SQLite')
conn <- dbConnect(drv = driver, file.name) #use the file you want to extract for file.name
mytable.beta <- dbReadTable(conn,"beta")
mytable.cov_mat <- dbReadTable(conn,"cov_mat")
dbDisconnect(conn)
  • Download R scores for each model here

Results

Ten psychiatric/disorder diseases

Here we provide QTWAS results on the summary statistics from ten GWAS studies on brain disorders, including five neuropsychiatric traits: schizophrenia (SCZ1), attention-deficit/hyperactivity disorder (ADHD2), bipolar disorder (BD3), autism spectrum disorder (ASD4) and major depressive disorder (MDD5); and four neurodegenerative traits: Alzheimer’s disease (AD_Kunkle6 and AD_Jansen7), Parkinson’s disease (PD8), multiple sclerosis (MS9) and amyotrophic lateral sclerosis (ALS10).

We also developed a Shiny app to visualize the results: tianyingw.shinyapps.io/QTWAS/.

797 UK Biobank traits

We also provide QTWAS results on 797 UK Biobank continuous phenotypes with their summary statistics on 28 million imputed variants. We provide phenome-wide results for genes, genome-wide gene-based results for each trait with respect to all 49 tissues separately.

References

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