README.md

In zhuchcn/ShinyMetabase: A shiny application for metabolomics data analysis

ShinyMetabase

This R package is a wrap up of a shiny app for Metabolomics data analysis. This app was built on top of the Metabase package, with a GUI interface provided by the shiny framework. It provides some fundamental types of analysis, including univariate analysis (linear model), principle component analysis (PCA), clustered heatmap, and partial correlation network analysis.

Installation

There are quite a few packages that ShinyMetabase depends on. Please make sure all dependency packages were installed in your R environment. Using the command provided below to find out which packages are not installed.

pkgs = c(
    "shiny", "shinydashboard", "dplyr", "reshape2", "glue", "ggplot2", 
    "R6", "DT", "shinyPagerUI", "shinyjs", "plotly", "heatmaply", "shinyjqui",
    "space", "Metabase", "ggmetaplots"
)
for(pkg in pkgs){
    if(!suppressPackageStartupMessages(require(pkg, character.only = TRUE))){
        print(paste0("Package not installed: ", pkg))
    }
}

All packages can be installed from CRAN using the install.packages() function, except the Metabase, ggmetaplots and shinyPagerUI must be installed from github:

devtools::install_github("zhuchcn/Metabase")
devtools::install_github("zhuchcn/ggmetaplots")
devtools::install_github('wleepang/shiny-pager-ui')

When all dependency packages are installed, the package can be installed from github.

devtools::install_github("zhuchcn/ShinyMetabase")

Data type

There are two entry points of this app. Users can either directly parse data to the launcher, or upload .csv files after the app is lunched.

Parse data to launcher

The data to be parsed to the launcher must inherits from the mSet class from the Metabase package.

data = Metabase::lipid
ShinyMetabase::launch(data)

Upload data after launch

Users can also upload three separated '.csv' files after the app is launched. The three files:

1. Conc table: Must only contain numeric values with the first column and row being the name of each feature or sample.
2. Sample table: Each row contains the information of a sample. The number of row must equal to the number of samples in the conc table. The first column must be sample names and must equal to the sample names in the conc table
3. Feature data: Each row contains the inforamtion of a feature. The number of row must equal to the number of features in the conc table. THe first column must be feature names and must equal to the feature names in the conc table

Examples of the three .csv files can be found in this repository in inst/shiny-metabase/data/ or from the package:

list.files(system.file("shiny-metabase/data/", package="ShinyMetabase"), pattern = ".csv")

To launch the app without parsing any data, just simply run:

ShinyMetabase::launch()

zhuchcn/ShinyMetabase documentation built on May 3, 2019, 3:36 p.m.