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Rapid High-throughput Species Identification of Botanical Material Using Direct Analysis in Real Time High Resolution Mass Spectrometry

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Published on: October 2, 2016

Advanced heat map and clustering analysis using heatmap3.

Shilin Zhao¹, Yan Guo¹, Quanhu Sheng¹

¹Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA.

Biomed Research International

|August 22, 2014

Summary

This summary is machine-generated.

The R package heatmap3 enhances data visualization for expression analysis. It offers advanced, customizable heat maps and dendrograms, improving upon the basic heatmap function.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Heat maps and clustering are essential for expression analysis, data visualization, and quality control.
The standard R 'heatmap' function has limitations in customizability and advanced features.

Purpose of the Study:

To develop an R package, 'heatmap3', that overcomes the limitations of the existing 'heatmap' function.
To provide users with advanced, highly customizable heat map and dendrogram generation capabilities.

Main Methods:

The 'heatmap3' package is built upon the R 'heatmap' function, ensuring compatibility.
Key enhancements include customizable legends, side annotations, diverse color options, and multi-layer phenotype labeling.

Main Results:

'heatmap3' enables the creation of state-of-the-art, customizable heat maps and dendrograms.
New features include automated association tests based on phenotypes and various agglomeration methods for sample clustering.

Conclusions:

'heatmap3' offers a significant improvement over the basic 'heatmap' function for expression analysis.
The package provides powerful and convenient tools for advanced data visualization and quality control in R.