SPADEVizR: an R package for visualization, analysis and integration of SPADE results

• DOI: 10.1093/bioinformatics/btw708
• Publication Date: 2016-11-05T12:14:59Z
• Authors: Guillaume Gautreau; David Pejoski; Roger Le Grand; Antonio Cosma; Anne-Sophie Beignon; Nicolas Tchitchek
• Keywords: Mass cytometry; Hierarchical clustering

Flow, hyperspectral and mass cytometry are experimental techniques measuring cell marker expressions at the single level. The recent increase of number markers simultaneously measurable has led to development new automatic gating algorithms. Especially, SPADE algorithm been proposed as a novel way identify clusters cells having similar phenotypes in high-dimensional data. While or other clustering algorithms powerful approaches, complementary analysis features needed better characterize identified clusters.We have developed SPADEVizR, an R package designed for visualization, integration results. available statistical methods allow highlighting with relevant biological behaviors integrating them additional variables. Moreover, several visualization clusters, such volcano plots, streamgraphs, parallel coordinates, heatmaps, distograms. SPADEVizR can also generate linear, Cox random forest models predict outcomes, based on cluster abundances. Additionally, allowing quantify visualize quality These essential interpret identified clusters. Importantly, handle results from than SPADE.SPADEVizR is distributed under GPL-3 license https://github.com/tchitchek-lab/SPADEVizR [e-mail] data Bioinformatics online.