Examples of Accessible Functions

Firstly, assume you have already installed UCSCXenaShiny package.

library(UCSCXenaShiny)
#> =========================================================================================
#> UCSCXenaShiny version 1.1.5
#> Project URL: https://github.com/openbiox/UCSCXenaShiny
#> Usages: https://openbiox.github.io/UCSCXenaShiny/
#> 
#> If you use it in published research, please cite:
#>   Shixiang Wang, Yi Xiong, Longfei Zhao, Kai Gu, Yin Li, Fei Zhao, Jianfeng Li,
#>   Mingjie Wang, Haitao Wang, Ziyu Tao, Tao Wu, Yichao Zheng, Xuejun Li, Xue-Song Liu,
#>   UCSCXenaShiny: An R/CRAN Package for Interactive Analysis of UCSC Xena Data, 
#>   Bioinformatics, 2021;, btab561, https://doi.org/10.1093/bioinformatics/btab561.
#> =========================================================================================
#>                               --Enjoy it--

Fetch Data

We provide function to retrieve multi-dimensional data including genomic, epigenomic, transcriptomic, and proteomic data from TCGA (note, this actually contains data from TCGA/TARGET/GTEx databases) and CCLE Pan-Cancer dataset for single identifier (e.g., gene, protein).

Check parameters:

args(query_pancan_value)
#> function (molecule, data_type = c("mRNA", "transcript", "protein", 
#>     "mutation", "cnv", "cnv_gistic2", "methylation", "miRNA", 
#>     "fusion", "promoter", "APOBEC"), database = c("toil", "ccle", 
#>     "pcawg"), reset_id = NULL, ...) 
#> NULL

For TCGA gene expression data, we use Xena dataset with ID TcgaTargetGtex_rsem_gene_tpm which includes 19131 samples with tumor tissue samples and normal tissue samples. The expression value unit is log2(tpm+0.001).

Let’s check several examples.

Fetch Gene Expression

gene_expr <- query_pancan_value("TP53")
#> =========================================================================================
#> UCSCXenaTools version 1.4.7
#> Project URL: https://github.com/ropensci/UCSCXenaTools
#> Usages: https://cran.r-project.org/web/packages/UCSCXenaTools/vignettes/USCSXenaTools.html
#> 
#> If you use it in published research, please cite:
#> Wang et al., (2019). The UCSCXenaTools R package: a toolkit for accessing genomics data
#>   from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq.
#>   Journal of Open Source Software, 4(40), 1627, https://doi.org/10.21105/joss.01627
#> =========================================================================================
#>                               --Enjoy it--
#> Try querying data #1
#> -> Checking if the dataset has probeMap...
#> -> Done. ProbeMap is found.
#> More info about dataset please run following commands:
#>   library(UCSCXenaTools)
#>   XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_rsem_gene_tpm") %>% XenaBrowse()

str(gene_expr)
#> List of 2
#>  $ expression: Named num [1:19131] 4.79 5.89 5.52 4.43 2.38 ...
#>   ..- attr(*, "names")= chr [1:19131] "GTEX-S4Q7-0003-SM-3NM8M" "TCGA-19-1787-01" "TCGA-S9-A7J2-01" "GTEX-QV31-1626-SM-2S1QC" ...
#>   ..- attr(*, "label")= chr "gene expression RNAseq"
#>  $ unit      : chr "log2(tpm+0.001)"

Fetch Transcript Expression

transcript_expr <- query_pancan_value("ENST00000000233", data_type = "transcript")

Fetch Gene CNV

gene_cnv <- query_pancan_value("TP53", data_type = "cnv")

Fetch Gene Mutation

gene_mut <- query_pancan_value("TP53", data_type = "mutation")

Fetch miRNA mature strand expression

miRNA_expr <- query_pancan_value("hsa-let-7a-2-3p", data_type = "miRNA")

Data Visualization

Visualize Single Gene Expression in PANCAN Dataset

vis_toil_TvsN(Gene = "TP53", Mode = "Violinplot", Show.P.value = FALSE, Show.P.label = FALSE)
#> More info about dataset please run following commands:
#>   library(UCSCXenaTools)
#>   XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_rsem_gene_tpm") %>% XenaBrowse()

Compare Gene Expression Level in Single Cancer Type

vis_toil_TvsN_cancer(
  Gene = "TP53",
  Mode = "Violinplot",
  Show.P.value = TRUE,
  Show.P.label = TRUE,
  Method = "wilcox.test",
  values = c("#DF2020", "#DDDF21"),
  TCGA.only = FALSE,
  Cancer = "ACC"
)
#> More info about dataset please run following commands:
#>   library(UCSCXenaTools)
#>   XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_rsem_gene_tpm") %>% XenaBrowse()
#> Counting P value
#> Counting P value finished

Compare Gene Expression Level in Different Anatomic Regions

This function needs gganatogram package, which is not on CRAN. Please install it before using this function.

if (require("gganatogram")) {
  vis_pancan_anatomy(Gene = "TP53", Gender = c("Female", "Male"), option = "D")
}

Click to see the output

Visualize Relationship between Gene Expression and Prognosis in the PANCAN Dataset

vis_unicox_tree(
  Gene = "TP53",
  measure = "OS",
  threshold = 0.5,
  values = c("grey", "#E31A1C", "#377DB8")
)
#> More info about dataset please run following commands:
#>   library(UCSCXenaTools)
#>   XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_rsem_gene_tpm") %>% XenaBrowse()
#> Get data value for TP53

Other Functions and Data

All exported data and functions are organized at here.