---
output: github_document
knit: (function(inputFile, encoding) {
  rmarkdown::render(inputFile, encoding = encoding, output_dir = "../../") })
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  cache = TRUE,
  out.width = "100%"
)
options(tibble.print_min = 5, tibble.print_max = 5)
```

# cBioPortalData

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## cBioPortal data and MultiAssayExperiment

### Overview

The `cBioPortalData` R package aims to import cBioPortal datasets as
[MultiAssayExperiment][1] objects into Bioconductor. Some of the features of
the package include:

1. The use of the `MultiAssayExperiment` integrative container for coordinating
and representing the data.
2. The data container explicitly links all assays to the patient
clinical/pathological data.
3. With a [flexible API][2], `MultiAssayExperiment` provides harmonized
subsetting and reshaping into convenient wide and long formats.
4. The package provides datasets from both the API and the saved packaged data.
5. It also provides automatic local caching, thanks to [BiocFileCache][3].

[1]: http://bioconductor.org/packages/MultiAssayExperiment/
[2]: https://github.com/waldronlab/MultiAssayExperiment/wiki/MultiAssayExperiment-API
[3]: https://bioconductor.org/packages/BiocFileCache/

## MultiAssayExperiment Cheatsheet

<a href="https://github.com/waldronlab/cheatsheets/blob/master/MultiAssayExperiment_QuickRef.pdf">
<img src="https://raw.githubusercontent.com/waldronlab/cheatsheets/master/pngs/MultiAssayExperiment_QuickRef.png" width="989" height="1091"/>
</a>

## Quick Start

### Installation

To install from Bioconductor (recommended for most users, this will install the
release or development version corresponding to your version of Bioconductor):

```{r,eval=FALSE}
if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("cBioPortalData")
```

To install from GitHub (for bleeding-edge, not generally necessary because
changes here are also pushed to
[bioc-devel](https://www.bioconductor.org/developers/how-to/useDevel/).
Installing the development version and generally requires running
[bioc-devel](https://www.bioconductor.org/developers/how-to/useDevel/))

```{r,eval=FALSE}
if (!require("cBioPortalData", quietly = TRUE))
    BiocManager::install("waldronlab/cBioPortalData")
```

To load the package:

```{r,include=TRUE,results="hide",message=FALSE,warning=FALSE}
library(cBioPortalData)
```

```{r,results="hide",include=FALSE}
cbio <- cBioPortal()
studies <- getStudies(cbio, buildReport = TRUE)
st <- studies
packpct <- round(prop.table(table(st$pack_build))[[2]], 2) * 100
apipct <- round(prop.table(table(st$api_build))[[2]], 2) * 100
```

## Note

`cBioPortalData` is a work in progress due to changes in data curation and
cBioPortal API specification. Users can view the `data(studiesTable)` dataset
to get an overview of the studies that are available and currently building
as `MultiAssayExperiment` representations. About `r apipct` % of the studies via
the API (`api_build`) and `r packpct` % of the package studies (`pack_build`)
are building, these include additional datasets that were not previously
available. Feel free to file an issue to request prioritization of fixing any
of the remaining datasets.

```{r,eval=FALSE}
cbio <- cBioPortal()
studies <- getStudies(cbio, buildReport = TRUE)
```

```{r}
table(studies$api_build)

table(studies$pack_build)
```

### API Service

Flexible and granular access to cBioPortal data from `cbioportal.org/api`.
This option is best used with a particular gene panel of interest. It allows
users to download sections of the data with molecular profile and gene panel
combinations within a study.

```{r,warning=FALSE,message=FALSE,include=TRUE,results="hide"}
gbm <- cBioPortalData(api = cbio, by = "hugoGeneSymbol", studyId = "gbm_tcga",
    genePanelId = "IMPACT341",
    molecularProfileIds = c("gbm_tcga_rppa", "gbm_tcga_mrna")
)
```

```{r}
gbm
```

### Packaged Data Service

This function will download a dataset from the `cbioportal.org/datasets`
website as a packaged tarball and serve it to users as a `MultiAssayExperiment`
object. This option is good for users who are interested in obtaining
all the data for a particular study.

```{r,warning=FALSE,message=FALSE,include=TRUE,results="hide"}
acc <- cBioDataPack("acc_tcga")
```

```{r}
acc
```

