scRNA Desk - your single-cell QC metrics, read, filtered and routed to a model

Paste one per-cell quality-control metrics table from a single-cell RNA-seq dataset - barcode, sample or batch, condition, genes detected, total UMI counts, mitochondrial percentage, ribosomal and haemoglobin percentages, doublet score - and run two worksheets over it: the QC read that decides what to filter, and the scvi-tools integration setup that follows it. A free in-browser engine computes every distribution, applies MAD-based outlier detection on the log1p scale the way scverse best practice describes it, reports the retention each threshold would produce per sample, catches non-integer counts, mitochondrial values on the wrong scale, duplicated barcodes and ambient-RNA signatures, raises batch-condition confounding as critical, and routes an scvi-tools model from the declared modality and label state - then reconciles the model's worksheet against every one of those findings. Your expression matrix never leaves your machine; only the metrics table does. A derived work built on two community skills, credited in full: @anthropics/single-cell-rna-qc (the MAD filtering method, the metric set and the permissive-by-default posture) and @anthropics/scvi-tools (the model-selection tree, the raw-counts requirement and the covariate handling), both from @anthropics/knowledge-work-plugins. Not a diagnostic tool and not a statistical conclusion.

Every public app is built from a security-scanned skill and must pass a clean scan — skill and frontend — before it can be listed. Have a skill of your own? Turn it into an app — or read the step-by-step walkthrough.