The auxiliary commands which can help to the users

Selcen Ari

2022-04-26

library(ceRNAnetsim)

1. Introduction

In the other package vignettes, usage of ceRNAnetsim is explained in details. But in this vignette, some of commands which facitate to use of other vignettes.

2. Installation

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("ceRNAnetsim")

3. Selection of perturbing element from dataset

data("TCGA_E9_A1N5_tumor")
data("TCGA_E9_A1N5_normal")
data("mirtarbasegene")
data("TCGA_E9_A1N5_mirnanormal")

3.1. Selection of HIST1H3H gene at vignette How does the system behave in mirtarbase dataset without interaction factors?

3.2. Selection of ACTB gene at vignette How does the system behave in mirtarbase dataset without interaction factors?

4. Determination of ACTB gene perturbation efficiency with different expression level changes

Firstly, clean dataset as individual gene has one expression value. And then filter genes which have expression values greater than 10.

We can determine perturbation efficiency of an element on entire network as following:

On the other hand, the perturbation eficiency of ATCB gene is higher, when this gene is regulated with 30-fold upregulation like in HIST1H3H.

5. Session Info

sessionInfo()
#> R version 4.2.0 RC (2022-04-19 r82224)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 20.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /home/biocbuild/bbs-3.15-bioc/R/lib/libRblas.so
#> LAPACK: /home/biocbuild/bbs-3.15-bioc/R/lib/libRlapack.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_GB              LC_COLLATE=C              
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] ceRNAnetsim_1.8.0 tidygraph_1.2.1   dplyr_1.0.8      
#> 
#> loaded via a namespace (and not attached):
#>  [1] tidyselect_1.1.2   xfun_0.30          bslib_0.3.1        graphlayouts_0.8.0
#>  [5] purrr_0.3.4        listenv_0.8.0      colorspace_2.0-3   vctrs_0.4.1       
#>  [9] generics_0.1.2     viridisLite_0.4.0  htmltools_0.5.2    yaml_2.3.5        
#> [13] utf8_1.2.2         rlang_1.0.2        jquerylib_0.1.4    pillar_1.7.0      
#> [17] glue_1.6.2         DBI_1.1.2          tweenr_1.0.2       lifecycle_1.0.1   
#> [21] stringr_1.4.0      munsell_0.5.0      gtable_0.3.0       future_1.25.0     
#> [25] codetools_0.2-18   evaluate_0.15      knitr_1.38         fastmap_1.1.0     
#> [29] parallel_4.2.0     fansi_1.0.3        furrr_0.2.3        Rcpp_1.0.8.3      
#> [33] scales_1.2.0       jsonlite_1.8.0     farver_2.1.0       parallelly_1.31.1 
#> [37] gridExtra_2.3      ggforce_0.3.3      ggplot2_3.3.5      digest_0.6.29     
#> [41] stringi_1.7.6      ggrepel_0.9.1      polyclip_1.10-0    grid_4.2.0        
#> [45] cli_3.3.0          tools_4.2.0        magrittr_2.0.3     sass_0.4.1        
#> [49] tibble_3.1.6       ggraph_2.0.5       crayon_1.5.1       tidyr_1.2.0       
#> [53] pkgconfig_2.0.3    ellipsis_0.3.2     MASS_7.3-57        viridis_0.6.2     
#> [57] assertthat_0.2.1   rmarkdown_2.14     R6_2.5.1           globals_0.14.0    
#> [61] igraph_1.3.1       compiler_4.2.0