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Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore

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ClusterEnG: an interactive educational web resource for clustering and visualizing high-dimensional data.

Mohith Manjunath^1,2, Yi Zhang^1,2, Steve H Yeo²

¹Department of Bioengineering, University of Illinois at Urbana-Champaign,Urbana, IL 61801, USA.

Peerj. Computer Science

|March 26, 2019

Summary

This summary is machine-generated.

ClusterEnG offers a web resource for big data clustering with interactive visualizations, addressing the lack of integrated tools for data analysis and education on clustering algorithms.

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Area of Science:

Genomics
Bioinformatics
Data Science

Background:

Clustering is a fundamental data analysis technique for uncovering hidden patterns by grouping similar data points.
Existing tools often lack integrated state-of-the-art clustering methods and interactive visualization capabilities.
A gap exists for a comprehensive web resource combining advanced clustering with user-friendly data exploration.

Purpose of the Study:

To introduce ClusterEnG, a web resource designed for clustering big data.
To provide interactive visualizations, including 3D views and zoom features, for enhanced data exploration.
To educate users on the nuances and potential pitfalls of various clustering algorithms.

Main Methods:

Development of ClusterEnG as a web-based interface for clustering.
Integration of advanced clustering algorithms for big data analysis.
Implementation of interactive visualization tools such as 3D views and cluster selection functionalities.

Main Results:

ClusterEnG provides a unified platform for big data clustering.
Interactive visualizations facilitate intuitive understanding of data structures.
Educational components help users grasp algorithm differences and limitations.

Conclusions:

ClusterEnG bridges the gap for scientists lacking computational expertise, enabling intuitive data structure understanding.
The resource offers state-of-the-art clustering methods and interactive visualizations in a single platform.
It serves as a valuable tool for both data analysis and educational purposes in genomics and beyond.