Here we describe our single cell data explorer. This shiny application has been developped to analyze, vizualize and extract informations from single-cell sequencing datasets. ISCEBERG can transform raw counts into filtered, normalized counts and computes clustering, UMAP to provide a Seurat single-cell sequencing dataset from various input formats (H5, MTX, TXT or CSV). ISCEBERG allows the use of preprocessed RDS files as input containing already a Seurat single-cell sequencing dataset. The purpose of this application is to explore much deeper your single-cell datasets without using R code lines. Graphics and associated tables are downloadable. To ensure Reproducibility and Traceability, preprocessed and subclusterized data are provided as Seurat objects (to be re-analyzed or re-loaded later) with a report of all command lines used to generate them.

This work was supported by the Agence Nationale de la Recherche (ANR) grants "HSCreg" (ANR-21-CE14-0032-01) , "European Genomic Institute for Diabetes" E.G.I.D (ANR-10-849 LABX-0046), a French State fund managed by ANR under the frame program Investissements d'Avenir I-SITE ULNE / ANR-16-IDEX-0004 ULNE, by grants from the Fondation pour la Recherche Médicale (FRM : EQU202203014645) and by European Commission