Single-Cell Perturbation

Why This Exists

• Without it: perturbation screens often stop at naive grouping and miss responder versus non-responder structure.
• With it: the official pertpy Mixscape workflow computes perturbation signatures and classifies perturbed subpopulations.

Current Methods

1. mixscape

Key Inputs

• a perturbation-aware AnnData
• a perturbation column via --pert-key
• a control label via --control
• optional replicate / batch split via --split-by

Public Parameters

Parameter	Meaning
--method	currently mixscape
--pert-key	perturbation or guide label column in adata.obs
--control	control category in the perturbation column
--split-by	biological replicate or condition column
--n-neighbors	neighbors used for perturbation signature
--logfc-threshold	DE threshold used inside Mixscape
--pval-cutoff	DE p-value cutoff used inside Mixscape
--perturbation-type	expected perturbation label such as KO

Notes

• This wrapper uses the official pertpy.tools.Mixscape workflow.
• Mixscape is best suited for Perturb-seq or CRISPR perturbation screens with a clear control population.
• If the input AnnData does not already contain perturbation labels in adata.obs, prepare them upstream first; OmicsClaw now provides sc-perturb-prep for expression data plus barcode-to-guide mapping files.

Data / State Requirements

• Matrix: expects normalized expression (log1p); if raw counts are detected, the skill normalizes automatically
• Layers: layers["counts"] preserved when present
• Required metadata: a perturbation label column in adata.obs (default: perturbation) with a control label (default: NT)
• PCA: if X_pca is missing, the skill computes it automatically

Upstream Step

Run sc-perturb-prep first if you have raw expression + a barcode-to-sgRNA mapping file. If your AnnData already has perturbation labels in .obs, you can use it directly.

Workflow

1. Load input or generate demo data
2. Preflight: validate perturbation column and control label exist
3. Ensure PCA is available
4. Run Mixscape (perturbation signature + classification)
5. Detect degenerate output (all NP)
6. Persist results: processed.h5ad with contract metadata
7. Render gallery and export tables

Outputs

• processed.h5ad (canonical output with contract metadata)
• tables/mixscape_class_counts.csv
• tables/mixscape_global_class_counts.csv
• tables/mixscape_cell_classes.csv
• figures/mixscape_global_classes.png
• figure_data/ (plot-ready CSVs)
• reproducibility/commands.sh
• result.json and report.md

CLI Parameters

Flag	Type	Default	Description	Validation
--input	str	None	Input AnnData file (.h5ad)	Required unless --demo
--output	str	—	Output directory	Required
--demo	flag	off	Run with built-in demo data	—
--method	str	mixscape	Analysis method (currently only mixscape)	Choices: mixscape
--pert-key	str	perturbation	adata.obs column containing perturbation labels	Column must exist; perturbation + control values must be present
--control	str	NT	Control label value inside the --pert-key column	Must match a category in adata.obs[pert_key]
--split-by	str	replicate	adata.obs column for replicate/batch splitting	Optional
--n-neighbors	int	20	Neighbors used for perturbation signature computation	—
--logfc-threshold	float	0.25	Log fold-change threshold used inside Mixscape DE	—
--pval-cutoff	float	0.05	P-value cutoff used inside Mixscape DE	—
--perturbation-type	str	KO	Expected perturbation class label (e.g., KO, overexpression)	—
--seed	int	0	Random seed for reproducibility	—
--r-enhanced	flag	off	Generate R Enhanced plots (requires R + ggplot2)	—

R Enhanced Plots

Renderer	Output file	Description
plot_embedding_discrete	figures/r_enhanced/r_embedding_discrete.png	UMAP colored by Mixscape class assignment
plot_embedding_feature	figures/r_enhanced/r_embedding_feature.png	UMAP colored by perturbation score

Special Requirements

Perturbation Labels in adata.obs

--pert-key and --control are the two critical parameters for a real run:

• --pert-key must name an existing column in adata.obs that contains perturbation group labels (e.g., gene names or guide targets).
• --control must match the exact string used to label non-targeting control cells in that column (default NT).

If these labels are absent, run sc-perturb-prep first to merge a barcode-to-guide mapping file into the expression object.

# Typical real-data run
python omicsclaw.py run sc-perturb \
  --input perturb_prep_output/processed.h5ad \
  --pert-key perturbation \
  --control NT \
  --output results/

# If the column names differ from defaults
python omicsclaw.py run sc-perturb \
  --input data.h5ad \
  --pert-key guide_target \
  --control non-targeting \
  --output results/

Workflow Position

Upstream: sc-perturb-prep Downstream: sc-de (DE between perturbed and control), sc-enrichment