Last updated: 2018-09-16

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    File Version Author Date Message
    Rmd 8572f1a Xiang Zhu 2018-09-16 wflow_publish(“analysis/gene_set.Rmd”) 
data/
├── README.md
├── biological_pathway
│   ├── gene_37.3.mat
│   └── pathway.mat
└── tissue_set
    ├── de_genes
    ├── he_genes
    └── se_genes

5 directories, 3 files

Biological pathways

Tissue-based gene sets

The 113 GTEx tissue-based gene sets used in Zhu and Stephens (2017) are available in the folder tissue_set. There are 44 “highly expressed” (HE) gene sets, 49 “selectively expressed” (SE) gene sets and 20 “distincttively expressed” (DE) gene sets. The creation of SE sets uses a method described in Yang et al (2018). The creation of DE sets uses a method described in Dey et al (2017).

      44
      49
      20

Each of the tissue-based gene sets has the following format.

ensembl_gene_id chromosome_name start_position  end_position
ENSG00000002933 7   150497491   150502208
ENSG00000072778 17  7120444 7128592
ENSG00000075624 7   5566782 5603415
ENSG00000087086 19  49468558    49470135

Session information

R version 3.5.1 (2018-07-02)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] workflowr_1.1.1   Rcpp_0.12.18      digest_0.6.17    
 [4] rprojroot_1.3-2   R.methodsS3_1.7.1 backports_1.1.2  
 [7] git2r_0.23.0      magrittr_1.5      evaluate_0.11    
[10] stringi_1.2.4     whisker_0.3-2     R.oo_1.22.0      
[13] R.utils_2.7.0     rmarkdown_1.10    tools_3.5.1      
[16] stringr_1.3.1     yaml_2.2.0        compiler_3.5.1   
[19] htmltools_0.3.6   knitr_1.20

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