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 -0.9193220
```

Figure 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.