In this directory, we provide all the instructions for reproducing the GTEx results from: “Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions” (Urbut et al 2017).
rnorm(10)## [1] 0.5855288 0.7094660 -0.1093033 -0.4534972 0.6058875 -1.8179560
## [7] 0.6300986 -0.2761841 -0.2841597 -0.9193220Figure 3:Summary of primary patterns identified by mash in GTEx data
Figure 5:Histogram of Sharing
Figure 6:Pairwise sharing by magnitude of eQTL among tissues
Supplementary Figure 1:Sample sizes and effective sample sizes from mash analysis across tissues
Supplementary Figure 2:There are 4 figures here:
Summary of covariance matrices Uk with largest estimated weight (> 1%) in GTEx data:Uk2
Summary of covariance matrices Uk with largest estimated weight (> 1%) in GTEx data:Uk4
Summary of covariance matrices Uk with largest estimated weight (> 1%) in GTEx data:Uk5
Summary of covariance matrices Uk with largest estimated weight (> 1%) in GTEx data:Uk8
Supplementary Figure 3: Illustration of how Linkage Disequilibrium can impact effect estimate table and figure
Supplementary Figure 4:Pairwise Sharing By Sign
Supplementary Figure 5:Number of “tissue-specific eQTLs” in each tissues.
Supplementary Figure 6:Expression levels in genes with “tissue-specific eQTLs” are similar to those in other genes
Table 1: Heterogeneity Analysis Simulation and Data.