README.Rmd

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output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

# Overview

The `multiGSEA.shiny` package provides an interactive shiny applications that
enables users to explore the results of a gene set enrichment analysis performed
[`multiGSEA`](https://github.com/lianos/multiGSEA).

# Usage

More thorough documentation of the shiny application will be provided in the
near future in the form of a vignette, or more likely a screen cast.

In the meantime, this will just have to get you started:

```{r eval = FALSE}
library(multiGSEA.shiny)
vm <- exampleExpressionSet(dataset='tumor-vs-normal', do.voom=TRUE)
mg <- multiGSEA(gdb, vm, vm$design, "tumor", methods=c("camera", "fry"))
explore(mg)
```

The `explore` function will launch the application and load it with the
`MultiGSEAResult` object produced by the call to the `multiGSEA` function. You
can then explore the results of the "camera" or "fry" analysis through there.

Users can serialize `MultiGSEAResult` objects to `*.rds` files on their
filesystem, which can also be loaded individually once the application is
launched.

# Application Deployment

Analysts can simply launch the `multiGSEA.shiny::explore()` application from
their workstation, however these applications can also be deployed to a shiny
server.

## Docker

The [`inst/docker`](inst/docker) folder provides examples of how to containerize
and deploy this application in different contexts.

The [`Dockerfile-base`](inst/docker/Dockerfile-base) creates a
docker image that, when run, launches the shiny app on
`http://container.ip/multiGSEA` (ie. `http://localhost/multiGSEA`).

## ShinyProxy

The [`Dockerfile-shinyproxy`](inst/docker/Dockerfile-shinyproxy)
creates an image that can be deployed via a
[ShinyProxy server](https://www.shinyproxy.io/).

Notes on setting up a ShinyProxy server on AWS are provided in the
[`aws-ubuntu-deployment.md`](inst/docker/aws-ubuntu-deployment.md) file.

# Installation

The multiGSEA suite of package will soon be submitted to bioconductor and
installable via the recommended `biocLite` mechanism. In the meantime, these
packages can be installed like so:

```{r gh-installation, eval = FALSE}
# install.packages("devtools")
devtools::install_github("lianos/multiGSEA")
devtools::install_github("lianos/multiGSEA.shiny")
devtools::install_github("lianos/GeneSetDb.MSigDB.Hsapiens.v61")
devtools::install_github("lianos/GeneSetDb.MSigDB.Mmusculus.v61")
```