bioRxivBioinformaticsPreprint
Mercator: An R Package for Visualization ofDistance Matrices
Zachary B. AbramsiD, Caitlin E. CoombesiD, Suli LiiD, Kevin R. CoombesiD
Abstract
SummaryUnsupervised data analysis in many scientific disciplines is based on calculating distances between observations and finding ways to visualize those distances. These kinds of unsupervised analyses help researchers uncover patterns in large-scale data sets. However, researchers can select from a vast number of different distance metrics, each designed to highlight different aspects of different data types. There are also numerous visualization methods with their own strengths and weaknesses. To help researchers perform unsupervised analyses, we developed the Mercator R package. Mercator enables users to see important patterns in their data by generating multiple visualizations using different standard algorithms, making it particularly easy to compare and contrast the results arising from different metrics. By allowing users to select the distance metric that best fits their needs, Mercator helps researchers perform unsupervised analyses that use pattern identification through computation and visual inspection.\n\nAvailability and ImplementationMercator is freely available at the Comprehensive R Archive Network (https://cran.r-project.org/web/packages/Mercator/index.html)\n\nContactKevin.Coombes@osumc.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.
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