Abstract

BackgroundSingle cell gene expression assays have become a powerful tool with which to dissect heterogeneous populations. While methods and software exist to interrogate such data, what has been lacking is a unified solution combining analysis and visualisation which is also accessible and intuitive for use by non-bioinformaticians, as well as bioinformaticians.ResultsWe present the Single cell expression visualiser (SCExV), a webtool developed to expedite the analysis of single cell qRT-PCR data. SCExV is able to take any data matrix of Ct values as an input, but can handle files exported by the Fluidigm Biomark platform directly. In addition, SCExV also accepts and automatically integrates cell surface marker intensity values which are measured during index sorting. This allows the user to directly visualise relationships between a single cell gene expression profile and the immunophenotype of the interrogated cell.ConclusionsSCExV is a freely available webtool created to import, filter, analyse, and visualise single cell gene expression data whilst being able to simultaneously consider cellular immunophenotype. SCExV is designed to be intuitive to use whilst maintaining advanced functionality and flexibility in how analyses are performed.

Highlights

  • Single cell gene expression assays have become a powerful tool with which to dissect heterogeneous populations

  • The evaluation of gene expression at the single cell level can be used for a variety of applications in cell biology, including gene network reconstruction [1, 2] and the study of cell populations too rare to assay using bulkpopulation based approaches [3]

  • Single Cell expression Visualiser (SCExV) allows the import of index

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Summary

Results

We present an example study using data from murine myeloid-erythroid progenitor cells generated to demonstrate the utility of SCExV. Creating/managing cell groups The colouring scheme within heatmaps/violin/MDS plots denote groups of cells. Example analysis of murine blood progenitor cells 282 murine myeloid-erythroid progenitor cells were sorted as Lineage negative/low, cKit positive and Sca

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