bio-crispr-screens-crispresso-editing
Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-
npx skills add BioTender-max/awesome-bio-agent-skills --skill crispresso-editing --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Quantifies CRISPR editing outcomes using CRISPResso2 across Cas9-nuclease, base editors, prime editor, and multiple CRISPResso workflows. It covers single-amplicon, batch, pooled-amplicon, WGS off-target, and sample-comparison modes, generating per-edit-type frequencies, allele-frequency tables, and diagnostic plots. It helps quantify edits, distinguish target edits from bystanders and indel byproducts, and produce publication-grade reports. It also notes failure modes from misalignment or contamination.
How it works
The skill describes executing CRISPResso2 commands for various modes:
- For single-amplicon: CRISPResso with parameters like --amplicon_seq and --guide_seq, plus a quantification window and quality filters, producing mapping statistics, editing frequencies, allele tables, and plots.
- For multi-sample batch: CRISPRessoBatch with a batch_settings.tsv, running per-sample CRISPResso analyses in parallel and producing aggregated outputs.
- For pooled-amplicon: CRISPRessoPooled with an amplicon_file, de-multiplexing reads to amplicons and generating per-amplicon outputs.
- For WGS off-target: CRISPRessoWGS with --bam, --reference, and --regions_file to quantify edits at targeted regions.
- For base editors: run CRISPResso with --base_editor_output and specify conversion direction (e.g., --conversion_nuc_from and --conversion_nuc_to) and widen the quantification window to cover editing positions.
- For prime editors: provide --prime_editing_pegRNA_spacer_seq, --prime_editing_pegRNA_extension_seq, and --prime_editing_pegRNA_scaffold_seq; outputs include Prime_editing_outcomes.txt.
- Includes a Python parse example to extract mapping stats and editing metrics from CRISPResso outputs.
When to use it
Use when quantifying editing from amplicon sequencing, choosing the appropriate CRISPResso mode by design, distinguishing intended edits from bystanders and indel byproducts, debugging low-alignment runs, or generating publication-grade editing reports.
What it can touch
CRISPResso2 CLI tools are the primary touchpoints:
- CRISPResso
- CRISPRessoBatch
- CRISPRessoPooled
- CRISPRessoWGS
- CRISPRessoCompare (implied by mode decisions) The skill explicitly references outputs and file names generated by these tools, and a Python snippet to parse results.
Caveats
Mentions specific failure modes and limitations, including:
- Pooled-amplicon mode misassignment if amplicons share primer sequences.
- Base editor mode missing conversion flags leading to misclassification.
- Prime editor mode missing extension sequences causing undetectable edits.
- Low alignment rate due to amplicon design errors; high substitution with low indel may indicate contamination; bystander edits in base editing are real and should be reported.
- Scaffold incorporation and RTT length can affect prime editing outcomes; designs may need adjustment.
- Outputs assume CRISPResso2 compatibility (tested with CRISPResso2 2.2.14+ and certain Python/Pandas versions).
## Version Compatibility Reference examples tested with: CRISPResso2 2.2.14+ (pinellolab/CRISPResso2), pandas 2.2+, numpy 1.26+, matplotlib 3.8+. Before using code patterns, verify installed versions match. If versions differ: - CLI: `CRISPResso --version`; `CRISPRessoBatch --help`; `CRISPRessoPooled --help`; `CRISPRessoWGS --help`; `CRISPRessoCompare --help` - Python: `from CRISPResso2 import ...` If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying. ## CRISPResso2 Editing Quantification **"Quantify CRISPR editing from my amplicon sequencing"** -> Align amplicon reads against the reference, classify each read as unmodified / NHEJ / HDR / base-edited / prime-edited within the quantification window, and report per-edit-type frequencies, indel size distributions, allele-frequency tables, and substitution-position profiles. - CLI: `CRISPResso` -- single amplicon, single sample - CLI: `CRISPRessoBatch` -- multi-sample with per-sample parameters - CLI: `CRISPRessoPooled` -- multi-amplicon pooled amplicon sequencing - CLI: `CRISPRessoWGS` -- off-target quantification from whole-genome
- Version Compatibility
- CRISPResso2 Editing Quantification
- Mode Decision Tree
- The Quantification Window
- Single-Amplicon Cas9 Editing
- Base Editor Quantification
- Prime Editor Quantification
- Batch Mode (Multi-Sample, Same Amplicon)
- Pooled-Amplicon Mode
- WGS Off-Target Mode
- Parse Output in Python
- Failure Modes
- Low alignment rate (<50%)
- High substitution rate but low indel (Cas9 sample)
Default Cas9 setup Base editor: widen window to cover editing positions 4-8 CRISPResso \ Cytosine Base Editor (CBE): C->T conversion Adenine Base Editor (ABE): A->G conversion Output adds: Prime_editing_outcomes.txt - intended-edit vs scaffold-incorporation vs indel vs unmodified batch_settings.txt (tab-separated, headers required) name fastq_r1 fastq_r2 amplicon_seq guide_seq t0 t0_R1.fq.gz t0_R2.fq.gz ACGT... GUIDE
What does the bio-crispr-screens-crispresso-editing skill do?
Quantifies CRISPR editing outcomes with CRISPResso2 (Clement 2019 Nat Biotechnol) across Cas9-nuclease (indels, HDR), CBE and ABE base editors (target conversion + bystander), and prime editor (pegRNA-templated) modes. Covers single-amplicon (CRISPResso), multi-sample batch (CRISPRessoBatch), pooled-amplicon (CRISPRessoPooled), WGS off-target (CRISPRessoWGS), and sample-comparison (CRISPRessoCompare) workflows; quantification-window math that controls what is called edited; substitution-vs-indel diagnostic to distinguish BE from Cas9 contamination; MMEJ deletion pattern interpretation; allele-
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill crispresso-editing --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 135 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.