Comparison of visualisation tools for single-cell RNAseq data
Batuhan ÇakıriD, Martin PreteiD, Ni HuangiD, Stijn van DongeniD, Pınar PiriD, Vladimir Yu KiseleviD
Abstract
In the last decade, single cell RNAseq (scRNAseq) datasets have grown from a single cell to millions of cells. Due to its high dimensionality, the scRNAseq data contains a lot of valuable information, however, it is not always feasible to visualise and share it in a scientific report or an article publication format. Recently, a lot of interactive analysis and visualisation tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review and compare several of the currently available analysis and visualisation tools and benchmark those that allow to visualize the scRNAseq data on the web and share it with others. To address the problem of format compatibility for most visualisation tools, we have also developed a user-friendly R package, sceasy, which allows users to convert their own scRNAseq datasets into a specific data format for visualisation.
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