Interactive Platform for Statistical Computing

Interactive Platform for Statistical Computing is a tool designed by Helikar Lab (Computational Biology @ University of Nebraska-Lincoln) to provide a free web-based platform to perform various statistical computations without having any knowledge of the high level programming languages, which is required for most statistical technologies. Most statistical technologies require users to be familiar with the command line and/or some type of a higher level programming language, making statistics less accessible to those who are not familiar with these technologies.

Development

The project was introduced as a part of Google Summer of Code (GSoC) in 2015.
The first version of the project utilizes the R server to build web-based interactive statistical analyses. Specifically, the following statistical functions were implemented in the first phase: Tabular data upload/export/visualization, descriptive statistics, t-tests (single-sample, independent sample, paired), graphing (2D/3D scatter plots, line, bar charts, box plots, histograms) and one/multi-way ANOVA.

As part of the second phase in GSoC 2016, the focus was to implement the statistical functions such as clustering, classification, time series analysis, regression models, correlation & covariance computations, heatmaps and various other plots.

###Technologies

• R
• Javascript, jQuery
• React JS
• Data visualization packages such as D3, NVD3 js
• CSS3
• HTML5

###Quick Start

• Download the latest release.
• Clone the repository: git clone https://github.com/HelikarLab/StatisticalPlatform.git.

#start R terminal
sudo R

#install from github
library(devtools)
install_github("HelikarLab/StatisticalPlatform")

#open in single-user server
library(opencpu)
opencpu$browse("/library/StatisticalPlatfrom/www")

Features

Data Manipulation

• Tabular data upload/export (.csv files)
• Tabular data viewing and editing
• Data preprocessing (sorting, subset)

Analysis

• Descriptive Statistics (mean, beta, standard deviation, variance, skewness, kurtosis)
• t-tests (Welch, Student, Paired)
• One/Multi-way ANOVA
• QQ Plot
• Correlation and Covariance Plots
• Linear Regression
• Time Series Analysis

Plots

• Line plots
• Histogram
• Bar plots (simple, grouped & stacked)
• Scatter plot
• Box plots
• Scatter Matrix plot
• Heatmap

Clustering

• K-Means clustering
• Cluster dendogram

Contributors

Akram Mohammed amohammed3@unl.edu

Shubham Kumar shubhamkmr47@gmail.com

Vinit Ravishankar vinit.ravishankar@gmail.com