---
title: "The SpatialDatasets package"
author:
- name: Nicholas Robertson
  affiliation:
  - Sydney Precision Data Science Centre, University of Sydney, Australia; 
  - School of Mathematics and Statistics, University of Sydney, Australia
- name: Farhan Ameen
  affiliation:
  - Sydney Precision Data Science Centre, University of Sydney, Australia; 
  - School of Mathematics and Statistics, University of Sydney, Australia
- name: Alex Qin
  affiliation:
  - Sydney Precision Data Science Centre, University of Sydney, Australia; 
  - School of Mathematics and Statistics, University of Sydney, Australia;
  - Westmead Institute for Medical Research, University of Sydney, Australia
- name: Ellis Patrick
  affiliation:
  - Sydney Precision Data Science Centre, University of Sydney, Australia; 
  - School of Mathematics and Statistics, University of Sydney, Australia;
  - Westmead Institute for Medical Research, University of Sydney, Australia
package: SpatialDatasets
output: 
  BiocStyle::html_document
vignette: >
  %\VignetteIndexEntry{The SpatialDataset package}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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


# Introduction

The `SpatialData` package contains a collection of spatially-resolved omics datasets, which have been formatted into the [SpatialExperiment](https://bioconductor.org/packages/SpatialExperiment), [MoleculeExperiment](https://bioconductor.org/packages/MoleculeExperiment) or [CytoImageList](https://bioconductor.org/packages/cytomapper) Bioconductor classes, for use in examples, demonstrations, and tutorials. The datasets are from several different platforms including IMC, MIBI-TOF, Xenium, CosMx and MERFISH. They have been sourced from various publicly available sources. 


# Installation

To install the `SpatialDatasets` package from GitHub:

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

BiocManager::install("SpatialDatasets")
```


# Datasets

The package contains the following datasets:

- `spe_Keren_2018`: A study on triple negative breast cancer 
containing 40 samples measured using MIBI-TOF published by [Keren et al. (2018)](https://doi.org/10.1016/j.cell.2018.08.039). 

# Load data

The following examples show how to load the example datasets as `SpatialExperiment` objects in an R session.

There are two options for loading the datasets: either using named accessor functions or by querying the ExperimentHub database.


## Load using named accessors

```{r, message=FALSE}
library(SpatialExperiment)
library(SpatialDatasets)
```


### Keren et al. (2018)

A study on triple negative breast cancer 
containing 40 samples measured using MIBI-TOF published by [Keren et al. (2018)](https://doi.org/10.1016/j.cell.2018.08.039). 

```{r, message=FALSE}
# load object
spe <- spe_Keren_2018()

# check object
spe
```



# Generating objects from raw data files

For reference, we include code scripts to generate the `SpatialExperiment`, `MoleculeExperiment` or `CytoImageList` objects from the raw data files.

These scripts are saved in `/inst/scripts/` in the source code of the `SpatialData` package. The scripts include references and links to the data files from the original sources for each dataset.


# Session information

```{r}
sessionInfo()
```