---
title: "Single Cell Proteomics data sets."
author:
    - name: Laurent Gatto
    - name: Christophe Vanderaa
output:
    BiocStyle::html_document:
        self_contained: yes
        toc: true
        toc_float: true
        toc_depth: 2
        code_folding: show
date: "`r BiocStyle::doc_date()`"
package: "`r BiocStyle::pkg_ver('scp')`"
vignette: >
    %\VignetteIndexEntry{Data Package for Single Cell Proteomics}
    %\VignetteEngine{knitr::rmarkdown}
    %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html
)
```

# The `scpdata` package

`scpdata` disseminates mass spectrometry (MS)-based single-cell 
proteomics (SCP) data sets formatted using the `scp` data structure. 
The data structure is described in the 
[`scp` vignette](http://www.bioconductor.org/packages/release/bioc/vignettes/scp/inst/doc/scp.html).

In this vignette, we describe how to access the SCP data sets. To 
start, we load the `scpdata` package.
    
```{r load_scp, message = FALSE}
library("scpdata")
```

# Load data from `ExperimentHub`

The data is stored using the 
[`ExperimentHub`](https://bioconductor.org/packages/release/bioc/html/ExperimentHub.html) 
infrastructure. We first create a connection with `ExperimentHub`. 

```{r EH, message = FALSE}
eh <- ExperimentHub()
```

You can list all data sets available in `scpdata` using the query 
function.

```{r EH_query, message = FALSE}
query(eh, "scpdata")
```

Another way to get information about the available data sets is to 
call `scpdata()`. This will retrieve all the available metadata. For 
example, we can retrieve the data set titles along with the 
description to make an informed choice about which data set to choose.

```{r scpdata_fun}
info <- scpdata()
knitr::kable(info[, c("title", "description")])
```
To get one of the data sets (*e.g.* `dou2019_lysates`) you can either 
retrieve it using the `ExperimentHub` query function 

```{r download_EH}
scp <- eh[["EH3901"]]
scp
```

or you can the use the built-in functions from `scpdata` 

```{r download_scpdata}
scp <- dou2019_lysates()
scp
```

# Data sets information

Each data set has been extensively documented in a separate man page 
(*e.g.* `?dou2019_lysates`). You can find information about the data 
content, the acquisition protocol, the data collection procedure as 
well as the data sources and reference.

# Data manipulation 

For more information about manipulating the data sets, check the 
[`scp`](http://bioconductor.org/packages/release/bioc/html/scp.html) 
package. The `scp` 
[vignette](http://bioconductor.org/packages/release/bioc/vignettes/scp/inst/doc/scp.html) 
will guide you through a typical SCP data processing workflow. Once 
your data is loaded from `scpdata` you can skip section 2 
*Read in SCP data* of the `scp` vignette.

# Session information {-}

```{r setup2, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "",
    crop = NULL
)
```

```{r sessioninfo, echo=FALSE}
sessionInfo()
```