Import your raw or working datasets for processing or further analysis. Compatible with already-processed data from Seurat (.rds) or scanpy (.h5ad), or upload raw aligned data directly from CellRanger (10x) and STARsolo/Kallisto pipelines.
Turn raw counts into analyzable data with reproducibility built right into the dataset itself. Pre-built pipelines for simplicity and speed, fully customizable when you need flexibility.
Correct for technical artifacts between samples or integrate datasets from different experiments with a growing selection of linear embedding (Harmony, Seurat), graph-based (BBKNN) or deep learning (scVI) methods.
Pull novel datasets out of existing atlases. Re-cluster and re-analyze in minutes to pull new insight from old data.
Identify cell-type markers to label UMAP clusters, or run pseudobulk differential expression (DESeq2) between conditions.
Instantly write cell-type or condition metadata to your dataset, visible to all downstream processing and analysis.
Infer a continuous timeline of how your cell populations develop, change or diverge.
