# Examples of Accessible Functions

#### Shixiang Wang, Yi Xiong, Longfei Zhao, Kai Gu, Yin Li, Fei Zhao

#### 2026-05-05

Firstly, assume you have already installed UCSCXenaShiny package.

    library(UCSCXenaShiny)
    #> =========================================================================================
    #> UCSCXenaShiny version 2.2.1
    #> Project URL: https://github.com/openbiox/UCSCXenaShiny
    #> Usages: https://openbiox.github.io/UCSCXenaShiny/
    #>
    #> If you use it in published research, please cite:
    #>   Shensuo Li, Yuzhong Peng, Minjun Chen, Yankun Zhao, Yi Xiong, Jianfeng Li, Peng Luo,
    #>   Haitao Wang, Fei Zhao, Qi Zhao, Yanru Cui, Sujun Chen, Jian-Guo Zhou, Shixiang Wang,
    #>   Facilitating integrative and personalized oncology omics analysis with UCSCXenaShiny,
    #>   Communications Biology, 1200 (2024),  https://doi.org/10.1038/s42003-024-06891-2
    #> =========================================================================================
    #>                               --Enjoy it--

## Tutorial Book

From UCSCXenaShiny v2, we provide a comprehensive tutorial book for introducing how to use the datasets, functions, and the Shiny application.

## 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", "methylation", "miRNA", "fusion", "promoter",
    #>     "APOBEC"), database = c("toil", "ccle", "pcawg"), reset_id = NULL,
    #>     opt_pancan = .opt_pancan)
    #> 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 1.7.0
    #> 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.
    #> Saving data to file /var/folders/1w/371ktd8j0fv8mp_dsgtvssnw0000gn/T//RtmpkZADev/UCSCXenaShiny/4822f991b17cbdab3831c455be7620b2.rds
    #> 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)
    #> Reading cache data /var/folders/1w/371ktd8j0fv8mp_dsgtvssnw0000gn/T//RtmpkZADev/UCSCXenaShiny/4822f991b17cbdab3831c455be7620b2.rds
    #> More info about dataset please run following commands:
    #>   library(UCSCXenaTools)
    #>   XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_rsem_gene_tpm") %>% XenaBrowse()
    #> Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
    #> ℹ Please use tidy evaluation idioms with `aes()`.
    #> ℹ See also `vignette("ggplot2-in-packages")` for more information.
    #> ℹ The deprecated feature was likely used in the UCSCXenaShiny package.
    #>   Please report the issue at
    #>   <https://github.com/openbiox/UCSCXenaShiny/issues>.
    #> This warning is displayed once per session.
    #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
    #> generated.
    #> Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
    #> ℹ Please use `linewidth` instead.
    #> ℹ The deprecated feature was likely used in the UCSCXenaShiny package.
    #>   Please report the issue at
    #>   <https://github.com/openbiox/UCSCXenaShiny/issues>.
    #> This warning is displayed once per session.
    #> Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
    #> generated.

### 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"
    )
    #> Reading cache data /var/folders/1w/371ktd8j0fv8mp_dsgtvssnw0000gn/T//RtmpkZADev/UCSCXenaShiny/4822f991b17cbdab3831c455be7620b2.rds
    #> 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",
      values = c("grey", "#E31A1C", "#377DB8")
    )
    #> Reading cache data /var/folders/1w/371ktd8j0fv8mp_dsgtvssnw0000gn/T//RtmpkZADev/UCSCXenaShiny/4822f991b17cbdab3831c455be7620b2.rds
    #> 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.