RichR

Enrichment for Diseases in a Set of Genes

By Deisy Morselli Gysi in r packages gene enrichment disease association

February 13, 2019

It provides a list of genes associated to diseases (g2d$clean and g2d$complete) based on the following 4 publications (GS2D, Fontaine (2016) [doi:10.18547/gcb.2016.vol2.iss1.e33], DisGeNET, Pinero (2016) [doi:10.1093/nar/gkw943] Berto2016, Berto (2016) [doi:10.3389/fgene.2016.00031] and PsyGeNET, Sacristan (2015) [doi:10.1093/bioinformatics/btv301]). Those lists were combined and manually curated to have matching disease names. When provided a list of gene names, it calculates the disease enrichment of the gene set. The enrichment is calculated using proportion test and Fisher’s exact test. Adjusted fdr p-values are returned alongside with p-values combined using the Fisher’s method.

You can download the package from CRAN using:

install.packages('RichR')

Input data

The input data for RichR are: the Background, that is the list of genes to be used as background control, the Genes2Dis, a data.frame containing genes and association to phenotypes and disorders and Genes, a vector of genes that should be tested for enrichment.

We recommend using g2d$clean as Genes2Dis. This is a manually curated list of genes and association to disorders.

Usage

require(RichR)

## Loading required package: RichR

data('g2d')

g2d_clean = g2d$clean

The user can choose a particular disorder, or use the whole disease set to compare to

g2d_ASD = subset(g2d_clean, 
                 g2d_clean$Disease %in% c('AUTISM'))

Enrichment(Background = g2d_clean$Gene.symbol,
           Genes2Dis = g2d_ASD,
           Genes = g2d_ASD$Gene.symbol[1:100])

## Warning in prop.test(.): Chi-squared approximation may be incorrect

## Warning in metap::sumlog(x): Some studies omitted

##   Disease Gene.symbol OBS        Fisher Prop     FisherAdj PropAdj
## 1  AUTISM         627 100 8.768203e-132    0 8.768203e-132       0
##          weight
## 1 4.647789e-260

Session Info

sessionInfo()

## R version 4.1.0 (2021-05-18)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur 10.16
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.1/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     
## 
## other attached packages:
## [1] RichR_1.0.0
## 
## loaded via a namespace (and not attached):
##  [1] Rcpp_1.0.6          plyr_1.8.6          mathjaxr_1.4-0     
##  [4] bslib_0.2.5.1       compiler_4.1.0      jquerylib_0.1.4    
##  [7] tools_4.1.0         digest_0.6.27       jsonlite_1.7.2     
## [10] evaluate_0.14       lattice_0.20-44     rlang_0.4.11       
## [13] Matrix_1.3-4        parallel_4.1.0      yaml_2.2.1         
## [16] mvtnorm_1.1-1       blogdown_1.3        xfun_0.23          
## [19] metap_1.4           stringr_1.4.0       knitr_1.33         
## [22] sass_0.4.0          multtest_2.48.0     stats4_4.1.0       
## [25] grid_4.1.0          Biobase_2.52.0      R6_2.5.0           
## [28] plotrix_3.8-1       Rdpack_2.1.2        survival_3.2-11    
## [31] rmarkdown_2.8.5     sn_2.0.0            bookdown_0.22      
## [34] multcomp_1.4-17     TH.data_1.0-10      reshape2_1.4.4     
## [37] TFisher_0.2.0       magrittr_2.0.1      BiocGenerics_0.38.0
## [40] codetools_0.2-18    MASS_7.3-54         htmltools_0.5.1.1  
## [43] rbibutils_2.2       mutoss_0.1-12       splines_4.1.0      
## [46] mnormt_2.0.2        numDeriv_2016.8-1.1 sandwich_3.0-1     
## [49] stringi_1.6.2       tmvnsim_1.0-2       zoo_1.8-9

Posted on:: February 13, 2019

Length:: 2 minute read, 392 words

Categories:: r packages gene enrichment disease association

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