MicroScope : comprehensive genome analysis software suite for gene expression heatmaps

Correspondence: b.khomtchouk@med.miami.edu Center for Therapeutic Innovation and Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, 1120 NW 14th ST, Miami, FL, USA 33136 Full list of author information is available at the end of the article Abstract We propose a user-friendly, comprehensive genome software suite for the interactive visualization and analysis of gene expression heatmaps, including integrated features to support: statistical analysis, gene ontology analysis, and dynamic network visualization of differentially expressed genes directly from a heatmap. MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: https://microscope.shinyapps.io/microscope. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope.


INTRODUCTION
Currently existing heatmap software produce static heatmaps [1][2][3][4][5], with no features available to dynamically interact with and explore the landscape of a heatmap. Such a feature would allow the user to interact with the data in a visual manner in real-time, thereby * to whom correspondence should be addressed allowing for a deeper data exploration experience. An interactive, non-reproducible heatmap tool was previously employed in the study of the transcriptome of the Xenopus tropicalis genome [6]. However, no open-source, dynamic and interactive heatmap software has yet been proposed to explore an arbitrary user-specified input dataset. Likewise, currently existing heatmap software do not provide built-in, user-friendly statistical analysis features.

APPROACH
In this paper, we leverage R's d3heatmap [7], shiny [8], htmlwidgets [9], and RColorBrewer [10] libraries to create a dynamic, interactive heatmap web app called MicroScope, in recognition of the software's magnification utility (described in Results section). We employ the Bioconductor package edgeR [11] to create a oneclick, built-in, user-friendly statistical analysis feature that provides differential expression analysis of gene expression data. This 1 not peer-reviewed) is the author/funder. All rights reserved. No reuse allowed without permission.
The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/034694 doi: bioRxiv preprint first posted online Dec. 17, 2015; supplies the user with rank-based information about nominal pvalue, false discovery rate, fold change, and counts per million in order to establish which specific genes in the heatmap are differentially expressed to a high degree of statistical significance. All heatmaps and statistical analyses are generated within the R environment on the server-side, thereby completely obviating the need for any programming skills on the client-side.

RESULTS
MicroScope is an R Shiny and JavaScript (D3.js) software program designed to produce dynamic, interactive heatmaps in a web browser. Figure 1 shows the UI in action. MicroScope allows the user to magnify any portion of a heatmap by a simple click-anddrag feature to zoom in, and a click-once feature to zoom out. MicroScope is designed with large heatmaps in mind (e.g., gene expression heatmaps with thousands of genes), where individual entries quickly become unreadable as more and more add up. However, MicroScope allows you to repeatedly zoom in to any sector of the heatmap to investigate a region, cluster, or even a single gene. You can scroll up and down the page of your web browser to see more genes than automatically fit your window. MicroScope also allows you to hover the mouse pointer over any specific gene to show precise expression level details. Some of the user-friendly features of MicroScope include: • User-specified file input widget

CONCLUSION
We provide access to a user-friendly web app designed to produce dynamic and interactive heatmaps within the R programming environment, without any prerequisite programming skills required of the user. Our software tool aims to enrich the genomic data exploration experience by allowing for the ability to magnify any portion of a gene expression heatmap and thereby exploring specific gene regions along with their respective expression level details.
Coupled with a built-in analytics platform to pinpoint statistically significant differentially expressed genes, MicroScope presents a significant advance in heatmap visualization technology over current standard protocols.