---
title: " Vignettte providing an overview of the data in MOFAdata"
author: "Britta Velten and Ricard Argelaguet"
date: "`r Sys.Date()`"
output:
  BiocStyle::html_document:
    toc: false
bibliography: MOFAdata_references.bib
vignette: >
  %\VignetteIndexEntry{MOFAdata}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

The MOFAdata package contains several data sets to be used
for illustration pruposes in the R package MOFA. 
Please refer to the vignettes in the MOFA package,
where we explain in detail how MOFA can be trained on the data
and how the resulting model is to be analysed.

```{r, warning=FALSE, message=FALSE}
library(MOFAdata)
library(MultiAssayExperiment)
```

In MOFAdata we store the following data objects to be used with MOFA:

* Preprocessed data on 200 CLL patients with
mRNA, methylation, drug response and mutation profiles [@cllpaper],
used as input for MOFA in [@MOFApaper].

```{r, warning=FALSE, message=FALSE}
# Load data
# import list with mRNA, Methylation, Drug Response and Mutation data. 
data("CLL_data") 
lapply(CLL_data, dim) 

# Load sample metadata: Sex and Diagnosis
data("CLL_covariates")
head(CLL_covariates)
```

* scMT data: Preprocessed data on 87 single cells [@angermueller2016parallel],
profiled using single-cell methylation and transcriptome sequencing,
used as input to MOFA in  [@MOFApaper].

```{r, warning=FALSE, message=FALSE}
data("scMT_data") 
scMT_data
```

* other data include trained MOFA models for the above data sets
as analysed in [@MOFApaper] and REACTOME gene set information
[@fabregat2015reactome] to be used in the MOFA package
for gene set enrichment analysis of trained models.

# References