---
title: "Introduction"
date: "`r BiocStyle::doc_date()`"
vignette: >
  %\VignetteIndexEntry{"1. Introduction"}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_knit$set(progress = FALSE)
```


TCGAbiolinks is able to access The National Cancer Institute (NCI) Genomic Data Commons (GDC) thorough its  
[GDC Application Programming Interface (API)](https://gdc.cancer.gov/developers/gdc-application-programming-interface-api) 
to search, download and prepare relevant data for analysis in R. 

# News

- April 2022:
  - Started to add support for GENCODE v36 pipelines
  - Add stemness score functions
- December 2019: 
  - Added support to non TCGA/TARGET projects - https://rpubs.com/tiagochst/TCGAbiolinks_RNA-seq_new_projects
  - Added support to linked Omics data retrieval - https://rpubs.com/tiagochst/linkedOmics
  - Included Glioma classifier from GUI to the main package - https://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/classifiers.html
- Added support to BCR Biotab clinical files   
- Workshop materials (ATAC-seq, ELMER and TCGAbiolinks) were added to vignette (https://bioconductor.org/packages/devel/bioc/vignettes/TCGAbiolinks/inst/doc/index.html)

# Citation

If you use TCGAbiolinks, please cite:

* Colaprico, Antonio, et al. "TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data." Nucleic acids research 44.8 (2015): e71-e71.
* Silva, Tiago C., et al. "TCGA Workflow: Analyze cancer genomics and epigenomics data using Bioconductor packages." F1000Research 5 (2016). (https://f1000research.com/articles/5-1542/v2)
* Mounir, Mohamed, et al. "New functionalities in the TCGAbiolinks package for the study and integration of cancer data from GDC and GTEx." PLoS computational biology 15.3 (2019): e1006701. (https://doi.org/10.1371/journal.pcbi.1006701)

# Other useful links

* Gao, Galen F., et al. "Before and After: Comparison of Legacy and Harmonized TCGA Genomic Data Commons’ Data." Cell systems 9.1 (2019): 24-34. (https://doi.org/10.1016/j.cels.2019.06.006)

* TCGA Workflow Analyze cancer genomics and epigenomics data using Bioconductor packages: http://bioconductor.org/packages/TCGAWorkflow/

# Installation

You can install the stable version from [Bioconductor](http://bioconductor.org/packages/release/bioc/html/TCGAbiolinks.html).
If you are having issues with the stable version, try using the development version.

* Stable version:
```{r message=FALSE, warning=FALSE, eval=FALSE}
if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("TCGAbiolinks")
```

* Development version:
```{r message=FALSE, warning=FALSE, eval=FALSE}
if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("BioinformaticsFMRP/TCGAbiolinksGUI.data")
BiocManager::install("BioinformaticsFMRP/TCGAbiolinks")
```

# Question and issues

Please use [Github issues](https://github.com/BioinformaticsFMRP/TCGAbiolinks/issues) if you want to file bug reports or feature requests.

# Required libraries

The examples in this tutorial use the following libraries: 
```{r message=FALSE, warning=FALSE, include=TRUE}
library(TCGAbiolinks)
library(dplyr)
library(DT)
```

# Session info

```{r}
version
packageVersion("TCGAbiolinks")
```
