SingleCellMultiModal.Rmd

---
title: "SingleCellMultiModal Introduction"
date: "`r BiocStyle::doc_date()`"
vignette: |
  %\VignetteIndexEntry{SingleCellMultiModal Introduction}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
output:
    BiocStyle::html_document:
      toc_float: true
runtime: shiny
Package: SingleCellMultiModal
bibliography: MultiAssay.bib
---

# Installation

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

BiocManager::install("SingleCellMultiModal")
```

## Load packages

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

# Introduction

This package introduces a suite of single-cell multimodal landmark datasets for
benchmarking and testing multimodal analysis methods via the `ExperimentHub`
Bioconductor package. The scope of this package is to provide efficient access
to a selection of curated, pre-integrated, publicly available landmark datasets
for methods development and benchmarking.

## Representation

Users can obtain integrative representations of multiple modalities as a
`MultiAssayExperiment`, a common core Bioconductor data structure relied on by
dozens of multimodal data analysis packages. `MultiAssayExperiment` harmonizes
data management of multiple experimental assays performed on an overlapping set
of specimens. Although originally developed for patient data from multi-omics
cancer studies, the `MultiAssayExperiment` framework naturally applies also to
single cells. A schematic of the data structure can be seen below. In this
context, "patients" are replaced by "cells". We use `MultiAssayExperiment`
because it provides a familiar user experience by extending
`SummarizedExperiment` concepts and providing open ended compatibility with
standard data classes present in Bioconductor such as the
`SingleCellExperiment`.

```{r,echo=FALSE}
imgurl <- paste0(
    "https://github.com/waldronlab/MultiAssayExperiment/blob/",
    "c3c59a094e5a08111ee98b9f69579db5634d9fd4/vignettes/",
    "MultiAssayExperiment.png?raw=true"
)
knitr::include_graphics(
    path = imgurl
)
```

## Datasets

Here we show a table of available datasets from the `SingleCellMultiModal`
experiment data package:

```{r}
DT::datatable(
    SingleCellMultiModal::ontomap(),
    caption = "Available datasets in SingleCellMultiModal"
)
```

Note that each dataset has its own dedicated function that can also be invoked
with `SingleCellMultiModal()`. For example, the `SingleCellMultiModal()`
function can be used to access the `MultiAssayExperiment` object for the
`mouse_gastrulation` dataset:

```{r,eval=FALSE}
SingleCellMultiModal::SingleCellMultiModal("mouse_gastrulation")
```

but can also be called individually with the dedicated function, `scNMT()` (as
seen in the `function_name` column).

```{r}
scNMT(
    DataType = "mouse_gastrulation",
    modes = "*",
    version = "2.0.0",
    dry.run = TRUE
) |>
    knitr::kable()
```

# Individual vignettes

To see the technology specific vignettes, use the following command to list the
vignettes:

```{r,eval=FALSE}
help(package = "SingleCellMultiModal")
```

and click on

* <u>[User guides, package vignettes and other documentation.](http://localhost:8787/help/library/SingleCellMultiModal/doc/index.html)</u>

in the Help pane of RStudio. 

# Session Information

<details> <summary> Click to expand </summary>

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

</details>