---
title: "Introduction to the msigdbr package"
output:
  rmarkdown::html_vignette:
    keep_md: true
vignette: >
  %\VignetteIndexEntry{Introduction to the msigdbr package}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
# increase the screen width
options(width = 90)
# reduce the minimum number of characters for the tibble column titles
options(pillar.min_title_chars = 8)
```

## Overview

Performing pathway analysis is a common task in genomics and there are many available software tools, many of which are R-based.
Depending on the tool, it may be necessary to import the pathways into R, translate genes to the appropriate species, convert between symbols and IDs, and format the object in the required way.

The `msigdbr` R package provides Molecular Signatures Database (MSigDB) gene sets typically used with the Gene Set Enrichment Analysis (GSEA) software:

* in an R-friendly format (a data frame in a "long" format with one gene per row)
* for multiple frequently studied model organisms (human, mouse, rat, pig, fly, yeast, etc.)
* as both gene symbols and NCBI/Entrez Gene IDs (for better compatibility with pathway enrichment tools)
* that can be used in a script without requiring additional external files

## Installation

The package can be installed from CRAN.

```{r install-package, eval=FALSE}
install.packages("msigdbr")
```

## Usage

Load package.

```{r load-package, message=FALSE}
library(msigdbr)
```

Check the available species.

```{r show-species}
msigdbr_show_species()
```

Retrieve human genes for all gene sets in the database.

```{r get-human-all}
m_df = msigdbr(species = "Homo sapiens")
head(m_df)
```

Check the available collections and sub-collections.

```{r show-collections}
m_df %>% dplyr::distinct(gs_cat, gs_subcat) %>% dplyr::arrange(gs_cat, gs_subcat)
```

Retrieve mouse genes for just the hallmark collection gene sets.

```{r get-mouse-h}
m_df = msigdbr(species = "Mus musculus", category = "H")
head(m_df)
```

Retrieve mouse C2 (curated) CGP (chemical and genetic perturbations) gene sets.

```{r get-mouse-c2}
m_df = msigdbr(species = "Mus musculus", category = "C2", subcategory = "CGP")
head(m_df)
```

The `msigdbr()` function output can also be manipulated as any standard data frame.

```{r get-mouse-h-filter}
m_df = msigdbr(species = "Mus musculus") %>% dplyr::filter(gs_cat == "H")
head(m_df)
```

## Integrating with Pathway Analysis Packages

Use the gene sets data frame for `clusterProfiler` (for genes as Entrez Gene IDs).

```{r cp-entrez, eval=FALSE}
m_t2g = m_df %>% dplyr::select(gs_name, entrez_gene) %>% as.data.frame()
enricher(gene = gene_ids_vector, TERM2GENE = m_t2g, ...)
```

Use the gene sets data frame for `clusterProfiler` (for genes as gene symbols).

```{r cp-symbols, eval=FALSE}
m_t2g = m_df %>% dplyr::select(gs_name, gene_symbol) %>% as.data.frame()
enricher(gene = gene_symbols_vector, TERM2GENE = m_t2g, ...)
```

Use the gene sets data frame for `fgsea`.

```{r fgsea, eval=FALSE}
m_list = m_df %>% split(x = .$gene_symbol, f = .$gs_name)
fgsea(pathways = m_list, ...)
```

## Questions and Concerns

Which version of MSigDB was used?

> This package was generated with MSigDB v7.1 (released March 2020).
> The MSigDB version is used as the base of the package version.
> You can check the installed version with `packageVersion("msigdbr")`.

Can I download the gene sets directly from MSigDB instead of using this package?

> Yes.
> You can then import the GMT files (with `getGmt()` from the `GSEABase` package, for example).
> The GMTs only include the human genes, even for gene sets generated from mouse data.
> If you are not working with human data, you then have to convert the MSigDB genes to your organism or your genes to human.

Can I convert between human and mouse genes just by adjusting gene capitalization?

> That will work for most genes, but not all.

Can I convert human genes to any organism myself instead of using this package?

> Yes.
> A popular method is using the `biomaRt` package.
> You may still end up with dozens of homologs for some genes, so additional cleanup may be helpful.

Aren't there already other similar tools?

> There are a few other resources that and provide some of the functionality and served as an inspiration for this package.
> [Ge Lab Gene Set Files](http://ge-lab.org/#/data) has GMT files for many species.
> [WEHI](http://bioinf.wehi.edu.au/software/MSigDB/) provides MSigDB gene sets in R format for human and mouse, but the genes are provided only as Entrez IDs and each collection is a separate file.
> [MSigDF](https://github.com/stephenturner/msigdf) is based on the WEHI resource, so it provides the same data, but converted to a more tidyverse-friendly data frame.
> When `msigdbr` was initially released, all of them were multiple releases behind the latest version of MSigDB, so they are possibly no longer maintained.

## Details

The Molecular Signatures Database (MSigDB) is a collection of gene sets originally created for use with the Gene Set Enrichment Analysis (GSEA) software.

Gene homologs are provided by HUGO Gene Nomenclature Committee at the European Bioinformatics Institute which integrates the orthology assertions predicted for human genes by eggNOG, Ensembl Compara, HGNC, HomoloGene, Inparanoid, NCBI Gene Orthology, OMA, OrthoDB, OrthoMCL, Panther, PhylomeDB, TreeFam and ZFIN.
For each human equivalent within each species, only the ortholog supported by the largest number of databases is used.


