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bioRxiv · 10.1101/2020.12.11.421883

Cytosplore-Transcriptomics: a scalable inter-active framework for single-cell RNA sequenc-ing data analysis

Abdelaal, T.·Eggermont, J.·Hollt, T.·Mahfouz, A.·Reinders, M.·Lelieveldt, B.
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Abstract

The ever-increasing number of analyzed cells in Single-cell RNA sequencing (scRNA-seq) experiments imposes several challenges on the data analysis. Current analysis methods lack scalability to large datasets hampering interactive visual exploration of the data. We present Cytosplore-Transcriptomics, a framework to analyze scRNA-seq data, including data preprocessing, visualization and downstream analysis. At its core, it uses a hierarchical, manifold preserving representation of the data that allows the inspection and annotation of scRNA-seq data at different levels of detail. Consequently, Cytosplore-Transcriptomics provides interactive analysis of the data using low-dimensional visualizations that scales to millions of cells. AvailabilityCytosplore-Transcriptomics can be freely downloaded from transcriptomics.cytosplore.org Contactb.p.f.lelieveldt@lumc.nl

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Abdelaal, T., Eggermont, J., Hollt, T., Mahfouz, A., Reinders, M., Lelieveldt, B.. 2020-12-12. Cytosplore-Transcriptomics: a scalable inter-active framework for single-cell RNA sequenc-ing data analysis. https://doi.org/10.1101/2020.12.11.421883

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