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. 2017 Mar 1;33(5):776-778.
doi: 10.1093/bioinformatics/btw707.

CymeR: cytometry analysis using KNIME, docker and R

Affiliations

CymeR: cytometry analysis using KNIME, docker and R

B Muchmore et al. Bioinformatics. .

Abstract

Summary: Here we present open-source software for the analysis of high-dimensional cytometry data using state of the art algorithms. Importantly, use of the software requires no programming ability, and output files can either be interrogated directly in CymeR or they can be used downstream with any other cytometric data analysis platform. Also, because we use Docker to integrate the multitude of components that form the basis of CymeR, we have additionally developed a proof-of-concept of how future open-source bioinformatic programs with graphical user interfaces could be developed.

Availability and implementation: CymeR is open-source software that ties several components into a single program that is perhaps best thought of as a self-contained data analysis operating system. Please see https://github.com/bmuchmore/CymeR/wiki for detailed installation instructions.

Contact: brian.muchmore@genyo.es or marta.alarcon@genyo.es.

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Figures

Fig. 1.
Fig. 1.
A screen shot showing the CymeR interface for Destiny on the top and three CymeR scatterplots of the same mass cytometry data colored and sized by a single attribute on the bottom. The bottom-left scatterplot shows the data represented by the first two diffusion components found by the Destiny algorithm while the bottom-center scatterplot shows the data represented by two t-SNE dimensions. The bottom-right scatterplot shows the data represented by the two t-SNE dimensions in the x and y dimensions and by the first diffusion component in the z dimension. The bottom-center scatterplot was also highlighted for cells positive for the chosen attribute, which immediately propagated to all other views of the same data (Color version of this figure is available at Bioinformatics online.)

References

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