---
title: "UCSCXenaTools: an R package for Accessing Genomics Data from UCSC Xena platform, from Cancer Multi-omics to Single-cell RNA-seq"
author: "Shixiang Wang \\
ShanghaiTech University"
date: "`r Sys.Date()`"
output:
prettydoc::html_pretty:
toc: true
theme: cayman
highlight: github
pdf_document:
toc: true
vignette: >
%\VignetteIndexEntry{Basic usage}
%\VignetteEngine{knitr::rmarkdown}
%\usepackage[utf8]{inputenc}
---
```{r setup, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
```
**UCSCXenaTools** is an R package for accessing genomics data from UCSC Xena platform,
from cancer multi-omics to single-cell RNA-seq.
Public omics data from UCSC Xena are supported through [**multiple turn-key Xena Hubs**](https://xenabrowser.net/datapages/), which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.
**Who is the target audience and what are scientific applications of this package?**
* Target Audience: cancer and clinical researchers, bioinformaticians
* Applications: genomic and clinical analyses
## Installation
Install stable release from CRAN with:
```{r, eval=FALSE}
install.packages("UCSCXenaTools")
```
You can also install devel version of **UCSCXenaTools** from github with:
```{r gh-installation, eval = FALSE}
# install.packages("remotes")
remotes::install_github("ropensci/UCSCXenaTools")
```
If you want to build vignette in local, please add two options:
```{r, eval=FALSE}
remotes::install_github("ropensci/UCSCXenaTools", build_vignettes = TRUE, dependencies = TRUE)
```
The minimum versions to run the vignette is `1.2.4`.
[GitHub Issue](https://github.com/ropensci/UCSCXenaTools/issues) is a place for discussing any problem.
## Data Hub List
All datasets are available at .
Currently, **UCSCXenaTools** supports the following data hubs of UCSC Xena.
* UCSC Public Hub:
* TCGA Hub:
* GDC Xena Hub:
* ICGC Xena Hub:
* Pan-Cancer Atlas Hub:
* UCSC Toil RNAseq Recompute Compendium Hub:
* PCAWG Xena Hub:
* ATAC-seq Hub:
* Singel Cell Xena Hub:
* Kids First Xena Hub:
* Treehouse Xena Hub:
Users can update dataset list from the newest version of UCSC Xena by hand with `XenaDataUpdate()` function, followed
by restarting R and `library(UCSCXenaTools)`.
If any url of data hub is changed or a new data hub is online, please remind me by emailing to or [opening an issue on GitHub](https://github.com/ropensci/UCSCXenaTools/issues).
## Usage
Download UCSC Xena datasets and load them into R by **UCSCXenaTools** is a workflow with `generate`, `filter`, `query`, `download` and `prepare` 5 steps, which are implemented as `XenaGenerate`, `XenaFilter`, `XenaQuery`, `XenaDownload` and `XenaPrepare` functions, respectively. They are very clear and easy to use and combine with other packages like `dplyr`.
To show the basic usage of **UCSCXenaTools**, we will download clinical data of LUNG, LUAD, LUSC from TCGA (hg19 version) data hub.
### XenaData data.frame
**UCSCXenaTools** uses a `data.frame` object (built in package) `XenaData` to generate an instance of `XenaHub` class, which records information of all datasets of UCSC Xena Data Hubs.
You can load `XenaData` after loading `UCSCXenaTools` into R.
```{r}
library(UCSCXenaTools)
data(XenaData)
head(XenaData)
```
### Workflow
Select datasets.
```{r}
# The options in XenaFilter function support Regular Expression
XenaGenerate(subset = XenaHostNames=="tcgaHub") %>%
XenaFilter(filterDatasets = "clinical") %>%
XenaFilter(filterDatasets = "LUAD|LUSC|LUNG") -> df_todo
df_todo
```
Sometimes we only know some keywords, `XenaScan()` can be used to scan all rows to detect if
the keywords exist in `XenaData`.
```{r}
x1 = XenaScan(pattern = 'Blood')
x2 = XenaScan(pattern = 'LUNG', ignore.case = FALSE)
x1 %>%
XenaGenerate()
x2 %>%
XenaGenerate()
```
Query and download.
```{r}
XenaQuery(df_todo) %>%
XenaDownload() -> xe_download
```
Prepare data into R for analysis.
```{r}
cli = XenaPrepare(xe_download)
class(cli)
names(cli)
```
### Browse datasets
Create two XenaHub objects:
* `to_browse` - a XenaHub object containing a cohort and a dataset.
* `to_browse2` - a XenaHub object containing 2 cohorts and 2 datasets.
```{r}
XenaGenerate(subset = XenaHostNames=="tcgaHub") %>%
XenaFilter(filterDatasets = "clinical") %>%
XenaFilter(filterDatasets = "LUAD") -> to_browse
to_browse
XenaGenerate(subset = XenaHostNames=="tcgaHub") %>%
XenaFilter(filterDatasets = "clinical") %>%
XenaFilter(filterDatasets = "LUAD|LUSC") -> to_browse2
to_browse2
```
`XenaBrowse()` function can be used to browse dataset/cohort links using your default web browser.
At default, this function limits one dataset/cohort for preventing user to open too many links at once.
```{r,eval=FALSE}
# This will open you web browser
XenaBrowse(to_browse)
XenaBrowse(to_browse, type = "cohort")
```
```{r, error=TRUE}
# This will throw error
XenaBrowse(to_browse2)
XenaBrowse(to_browse2, type = "cohort")
```
When you make sure you want to open multiple links, you can set `multiple` option to `TRUE`.
```{r, eval=FALSE}
XenaBrowse(to_browse2, multiple = TRUE)
XenaBrowse(to_browse2, type = "cohort", multiple = TRUE)
```
## More usages
The core functionality has been described above.
I write more usages about this package in my website but not here
because sometimes package check will fail due to internet problem.
- [Introduction and basic usage of UCSCXenaTools](https://shixiangwang.github.io/home/en/tools/ucscxenatools-intro/) - [PDF](https://shixiangwang.github.io/home/en/tools/ucscxenatools-intro.pdf)
- [APIs of UCSCXenaTools](https://shixiangwang.github.io/home/en/tools/ucscxenatools-api/) - [PDF](https://shixiangwang.github.io/home/en/tools/ucscxenatools-api.pdf)
Read [Obtain RNAseq Values for a Specific Gene in Xena Database](https://shixiangwang.github.io/home/en/tools/ucscxenatools-single-gene/) to see how to get values for single gene. A use case for survival analysis based on single gene expression has been published on rOpenSci, please read
[UCSCXenaTools: Retrieve Gene Expression and Clinical Information from UCSC Xena for Survival Analysis](https://ropensci.org/technotes/2019/09/06/ucscxenatools-surv/).
## QA
### How to resume file from breakpoint
Thanks to the UCSC Xena team, the new feature 'resume from breakpoint' is added and
can be done by **XenaDownload()** with the `method` and `extra` flags specified.
Of note, the corresponding `wget` or `curl` command must be installed by your OS
and can be found by R.
The folliwng code gives a test example, the data can be viewed on [web page](https://xenabrowser.net/datapages/?dataset=TcgaTargetGtex_expected_count&host=https%3A%2F%2Ftoil.xenahubs.net&removeHub=https%3A%2F%2Fxena.treehouse.gi.ucsc.edu%3A443).
```r
library(UCSCXenaTools)
xe = XenaGenerate(subset = XenaDatasets == "TcgaTargetGtex_expected_count")
xe
xq = XenaQuery(xe)
# You cannot resume from breakpoint in default mode
XenaDownload(xq, destdir = "~/test/", force = TRUE)
# You can do it with 'curl' command
XenaDownload(xq, destdir = "~/test/", method = "curl", extra = "-C -", force = TRUE)
# You can do it with 'wget' command
XenaDownload(xq, destdir = "~/test/", method = "wget", extra = "-c", force = TRUE)
```
## Citation
Cite me by the following paper.
```
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
# For BibTex
@article{Wang2019UCSCXenaTools,
journal = {Journal of Open Source Software},
doi = {10.21105/joss.01627},
issn = {2475-9066},
number = {40},
publisher = {The Open Journal},
title = {The UCSCXenaTools R package: a toolkit for accessing genomics data from UCSC Xena platform, from cancer multi-omics to single-cell RNA-seq},
url = {http://dx.doi.org/10.21105/joss.01627},
volume = {4},
author = {Wang, Shixiang and Liu, Xuesong},
pages = {1627},
date = {2019-08-05},
year = {2019},
month = {8},
day = {5},
}
```
Cite UCSC Xena by the following paper.
```
Goldman, Mary, et al. "The UCSC Xena Platform for cancer genomics data
visualization and interpretation." BioRxiv (2019): 326470.
```
## Acknowledgments
This package is based on [XenaR](https://github.com/mtmorgan/XenaR), thanks [Martin Morgan](https://github.com/mtmorgan) for his work.