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Dashboard implementation of clustering analysis on user-uploaded data
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README.md

SparseData Cluster

Objective

The goal of this project is to build a beautiful parser of data that can interpret matrix data (with a specific use-case being gene expression matrices) and construct basic interactive plots for data exploration and preliminary analyses.

Get Started

Use the online version of SparseData Cluster. See Installation for details on installing locally.

Functionality

  • Upload : Upload your own flat files (comma, tab, or semi-colon delimited) for analysis.
  • Cluster : Pair-wise correlation is computed between observations (by default, rows of matrix input) and displayed as a heatmap. A summary of the matrix is also given as plain text.
  • Rank : Choose 2 observations to view an interactive table of the differences for each feature. Note that when data is log2 transformed during Upload, these will correspond to log fold changes.

Details

Installation

Dependencies

  • This App depends on installation of the following R packages: shiny (version >= 0.12.1), shinydashboard, shinyapps, markdown, gplots, RColorBrewer.

To Run:

Open app.R and run the code in an interactive R session in the same directory

Organization

The application is organized into separate files as follows:

  • app.R : The top-level application that sources the rest of the necessary files to build the app and calls the shinyApp function
  • global.R : Globally needed packages and global variables to share data across multiple embedded apps
  • header.R : constructs the header bar
  • sidebar.R : constructs the sidebar; specific pages are delineated here via the tabName function, and are similarly defined in body.R
  • body.R : page-level construction of each tabName specified in sidebar.R
  • server.R : provides interactivity and backend calculations

Acknowledgements

Stefan Avey constructed the underlying base, and Rob Amezquita applied a slick coat of paint on it.

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