The Driskell lab joins efforts to simplify single cell analysis as a searchable web resource. We hope to be a complimentary resource to these excellent websites.

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In 2015 the Rendl laboratory launched a website that allowed for easy query of flow sorted RNAseq data from flow sorted fibroblasts populations include dermal papillae as a companion website to Sennet et al. 2015 Dev Cell. This website is extremely useful in querying genes in fibroblast populations from E14.5 and P5 mouse skin.

The Kasper lab has produced some of the most useful web resources to query single cell RNA-seq data utilizing the SCANPY Python analysis tool. The lab has performed single cell RNA seq anlaysis on homeostatic epidermal cells (Joost et al. 2016) as well as a useful comparison of unsorted anagen and telogen skin (Joost et al. 2020), which also included the analysis of fibroblast populations.

The UCI Skin Center has produced a useful R based platform to host single-cell RNA-seq data. This has been quickly utilized by four publications. Analysis of sorted skin cells 12 days post wounds Guerrero et al. 2019. Unsorted murine skin at homeostatic conditions Takahashi et al. 2020 JID. Analysis of unsorted embyronic skin at E13.5 and E14.5 Gupta et al. 2019 Dev Cell. Finally, a comparison of regenerating and non-regenerating large wounds Gay et al. 2020.