sc-perturb-prep
DocumentsLoad when attaching cell-barcode → sgRNA assignments from a mapping TSV/CSV onto a Perturb-seq expression AnnData, producing standardised perturbation / sgRNA / target-gene obs columns. Skip when the AnnData already has perturbation labels (go straight to sc-perturb) or for raw guide-calling from FASTQ (use upstream demuxlet / cellranger guide pipelines).
How to use this skill
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sc-perturb-prep
When to use
The user has Perturb-seq expression data (10x h5 / matrix dir / h5ad) and an upstream barcode-to-sgRNA mapping table (TSV / CSV from demultiplex / cellranger / cellbender output) and needs them merged into a single AnnData with:
obs[--pert-key](defaultperturbation) — canonical perturbation labelobs[--sgrna-key](defaultsgRNA) — guide identifierobs[--target-key](defaulttarget_gene) — inferred target geneobs["assignment_status"]—single_guide/multi_guide/unassignedobs["n_sgrnas"]— count per cell
Single backend: mapping_tsv. Then chain to sc-perturb for Mixscape
classification. This skill does NOT infer guide identities from FASTQ
— bring an upstream assignment table.
Inputs & Outputs
| Input | Format | Required |
|---|---|---|
| Expression | .h5ad / 10x .h5 / 10x dir | yes (unless --demo) |
| Barcode → sgRNA mapping | .tsv / .csv (--mapping-file) | yes (unless --demo) |
| Column overrides | --barcode-column / --sgrna-column / --target-column / --sep | optional (auto-detect by default) |
| Output | Path | Notes |
|---|---|---|
| Standardised AnnData | processed.h5ad | adds obs["perturbation"] / obs["sgRNA"] / obs["target_gene"] / obs["assignment_status"] / obs["n_sgrnas"]; non-gene features removed from var |
| Per-cell assignments | tables/perturbation_assignments.csv | always |
| Status counts | tables/assignment_status_counts.csv | single_guide / multi_guide / unassigned tally |
| Perturbation tally | tables/perturbation_counts.csv | cells per perturbation label |
| Dropped multi-guide | tables/dropped_multi_guide_cells.csv | when multi-guide cells were dropped |
| Feature summary | tables/feature_type_summary.csv | gene vs non-gene feature breakdown |
| Figure | figures/perturbation_counts.png | always |
| Report | report.md + result.json | always |
Flow
- Load expression input via
smart_load; load mapping viaload_sgrna_mapping(auto-detect--sepif unset). - Strip non-gene features from
var(e.g., 10x guide / antibody capture rows). - Collapse mapping rows per cell: tag
single_guide/multi_guide/unassignedbased on row count. - Drop
multi_guidecells unless--keep-multi-guideis set. - Match each sgRNA against
--control-patterns(,-separated, includes default NT-style patterns); rewrite matches to--control-label(defaultNT). - Infer target gene from sgRNA ID via
--delimiter+--gene-position, OR use--target-columnfrom the mapping if provided. - Save standardised AnnData, tables, figure,
report.md,result.json.
Gotchas
- All preflight failures
raise SystemExit, notValueError.sc_perturb_prep.py:205raisesSystemExit("Provide --input or use --demo");:207raisesSystemExit("Perturbation preparation requires --mapping-file for real inputs. Generate barcode-to-guide assignments upstream first.")when--mapping-fileis missing on a real (non-demo) run. Wrappers expecting standardValueErrorneed to catchSystemExit. multi_guidecells are DROPPED by default. Step 4 in the flow filters them out unless--keep-multi-guideis passed.result.json["n_cells_multi_guide_dropped"](line 267 / 362) records the count. If your screen has high MOI on purpose (combinatorial perturbations),--keep-multi-guideis mandatory.- Target gene is inferred by default, not read from mapping. Without
--target-column, the script splits the sgRNA ID by--delimiter(default_) and takes token at--gene-position(default0). For sgRNA IDs likeEGFR_sg1this givesEGFR; for non-standard formats (sg-EGFR-1,EGFR.sg1) you must pass--delimiteraccordingly or supply--target-column. - Control matching is pattern-based, not exact.
--control-patterns(default fromDEFAULT_CONTROL_PATTERNS) is a comma-separated list — any sgRNA whose ID contains one of the patterns is rewritten to--control-label(defaultNT). False positives are possible if a real guide's ID contains a control-pattern substring; reviewtables/perturbation_assignments.csvafter the run. - Non-gene features in
varare silently removed only whenvar["feature_types"]exists.sc_perturb_prep.py:222callskeep_gene_expression_features(adata); the helper early-returns the unchanged AnnData iffeature_typesisn't avarcolumn (typical for user-loaded h5ads). When it IS present (e.g., 10x cellranger output), antibody-capture / guide-capture rows are stripped silently andresult.json["n_non_gene_features_removed"]records the count. A0value means either the column was absent or there were no non-gene rows to remove.
Key CLI
# Demo (synthetic expression + mapping)
python omicsclaw.py run sc-perturb-prep --demo --output /tmp/sc_perturb_prep_demo
# Real run with auto-detected mapping columns + delimiter
python omicsclaw.py run sc-perturb-prep \
--input cellranger/raw_feature_bc_matrix.h5 \
--mapping-file guide_assignments.tsv \
--output results/
# Custom column names + non-default delimiter
python omicsclaw.py run sc-perturb-prep \
--input expression.h5ad \
--mapping-file mapping.csv \
--barcode-column cell_id --sgrna-column guide_id --target-column gene \
--sep ',' --delimiter '-' --gene-position 1 \
--output results/
# Keep combinatorial multi-guide cells (high-MOI screens)
python omicsclaw.py run sc-perturb-prep \
--input expression.h5ad --mapping-file mapping.tsv \
--keep-multi-guide --output results/
See also
references/parameters.md— every CLI flag, mapping-file conventionsreferences/methodology.md— assignment status semantics; control-pattern matchingreferences/output_contract.md—obs["perturbation"]/obs["sgRNA"]/obs["target_gene"]/obs["assignment_status"]schema- Adjacent skills:
sc-count/sc-multi-count(upstream — produces the expression matrix; the mapping comes from cellranger / demuxlet output),sc-perturb(downstream — Mixscape classification on the standardised AnnData),sc-de(alternative downstream — direct DE between perturbed and control without Mixscape)