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npx versuz@latest install freedomintelligence-openclaw-medical-skills-skills-bio-crispr-screens-crispresso-editinggit clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills.gitcp OpenClaw-Medical-Skills/SKILL.MD ~/.claude/skills/freedomintelligence-openclaw-medical-skills-skills-bio-crispr-screens-crispresso-editing/SKILL.md---
name: bio-crispr-screens-crispresso-editing
description: CRISPResso2 for analyzing CRISPR gene editing outcomes. Quantifies indels, HDR efficiency, and generates comprehensive editing reports. Use when analyzing amplicon sequencing data from CRISPR editing experiments to assess editing efficiency.
tool_type: cli
primary_tool: CRISPResso2
---
## Version Compatibility
Reference examples tested with: CRISPResso2 2.2+, pandas 2.2+
Before using code patterns, verify installed versions match. If versions differ:
- Python: `pip show <package>` then `help(module.function)` to check signatures
- CLI: `<tool> --version` then `<tool> --help` to confirm flags
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 Analysis
**"Quantify CRISPR editing from my amplicon data"** → Analyze amplicon sequencing to measure indel frequencies, HDR efficiency, and frameshift rates from CRISPR gene editing experiments.
- CLI: `CRISPResso --fastq_r1 reads.fq --amplicon_seq ATGC --guide_seq GUIDE`
## Basic Analysis
**Goal:** Quantify CRISPR editing outcomes from amplicon sequencing of a single target site.
**Approach:** Align amplicon reads against the reference and guide sequences with CRISPResso, which reports indel frequencies, allele tables, and editing efficiency plots.
```bash
# Analyze single amplicon
CRISPResso \
--fastq_r1 sample_R1.fastq.gz \
--fastq_r2 sample_R2.fastq.gz \
--amplicon_seq AATGTCCCCCAATGGGAAGTTCATCTGGCACTGCCCACAGGTGAGGAGGTCATGATCCCCTTCTGGAGCTCCCAACGGGCCGTGGTCTGGTTCATCATCTGTAAGAATGGCTTCAAGAGGCTCGGCTGTGGTT \
--guide_seq CTGCCCACAGGTGAGGAGGT \
--output_folder crispresso_output \
--name sample1
# Output includes:
# - Editing efficiency statistics
# - Indel distribution
# - Allele frequency plots
```
## With HDR Template
```bash
# Analyze HDR editing
CRISPResso \
--fastq_r1 hdr_sample_R1.fastq.gz \
--fastq_r2 hdr_sample_R2.fastq.gz \
--amplicon_seq AATGTCCCCCAATGGGAAGTTCATCTGGCACTGCCCACAGGTGAGGAGGTCATGATCCCCTTCTGGAGCTCCCAACGGGCCGTGGTCTGGTTCATCATCTGTAAGAATGGCTTCAAGAGGCTCGGCTGTGGTT \
--guide_seq CTGCCCACAGGTGAGGAGGT \
--expected_hdr_amplicon_seq AATGTCCCCCAATGGGAAGTTCATCTGGCACTGCCCACAGGTGAGGAGGTCATGATCCCCTTCTGGAGCTCCCAACGGGCCGTGGTCTGGTTCATCATCTGTAAGAATGGCTTCAAGATGCTCGGCTGTGGTT \
--output_folder hdr_output \
--name hdr_sample
```
## Batch Analysis
**Goal:** Process multiple CRISPR editing samples in a single run.
**Approach:** Define a batch file listing sample names, FASTQ paths, amplicon sequences, and guide sequences, then run CRISPRessoBatch for parallel multi-sample analysis.
```bash
# Create batch file (tab-separated)
# batch.txt:
# name fastq_r1 fastq_r2 amplicon_seq guide_seq
# sample1 s1_R1.fq.gz s1_R2.fq.gz AMPLICON1 GUIDE1
# sample2 s2_R1.fq.gz s2_R2.fq.gz AMPLICON2 GUIDE2
CRISPRessoBatch \
--batch_settings batch.txt \
--output_folder batch_output \
--n_processes 8
```
## Pool Analysis (Multiple Guides)
```bash
# Analyze pooled amplicons
CRISPRessoPooled \
--fastq_r1 pooled_R1.fastq.gz \
--fastq_r2 pooled_R2.fastq.gz \
--amplicon_file amplicons.txt \
--output_folder pooled_output \
--n_processes 8
# amplicons.txt format:
# amplicon_name amplicon_seq guide_seq
```
## WGS Analysis
```bash
# Analyze off-target editing from WGS
CRISPRessoWGS \
--bam aligned.bam \
--reference genome.fa \
--regions_file targets.bed \
--output_folder wgs_output
```
## Parse Results in Python
**Goal:** Extract editing metrics from CRISPResso output for downstream analysis or reporting.
**Approach:** Load the mapping statistics and quantification files from the CRISPResso output directory, and parse the compressed allele frequency table for allele-level detail.
```python
import pandas as pd
import json
# Load mapping statistics
with open('crispresso_output/CRISPResso_mapping_statistics.txt') as f:
stats = {}
for line in f:
key, value = line.strip().split('\t')
stats[key] = value
print(f"Reads aligned: {stats['READS_ALIGNED']}")
print(f"Reads aligned %: {stats['READS_ALIGNED_PERCENTAGE']}")
# Load quantification
quant = pd.read_csv('crispresso_output/CRISPResso_quantification_of_editing_frequency.txt', sep='\t')
print(quant)
# Load allele frequency
alleles = pd.read_csv('crispresso_output/Alleles_frequency_table.zip', compression='zip', sep='\t')
print(f"Unique alleles: {len(alleles)}")
print(alleles.head(10))
```
## Key Output Files
```
CRISPResso_output/
├── CRISPResso_mapping_statistics.txt # Read mapping stats
├── CRISPResso_quantification_of_editing_frequency.txt # Summary
├── Alleles_frequency_table.zip # All allele sequences
├── CRISPResso_RUNNING_LOG.txt # Analysis log
├── Indel_histogram.png # Indel size distribution
├── Insertion_deletion_substitution.png # Edit type pie chart
├── Alleles_frequency_table.png # Top allele bar plot
└── CRISPResso2_info.json # Machine-readable summary
```
## Quantify Specific Outcomes
```bash
# Define expected outcomes
CRISPResso \
--fastq_r1 sample_R1.fastq.gz \
--amplicon_seq AMPLICON \
--guide_seq GUIDE \
--coding_seq CODING_REGION \
--quantification_window_size 5 \
--quantification_window_center -3 \
--output_folder output
```
## Base Editing Analysis
```bash
# For base editors (CBE/ABE)
CRISPResso \
--fastq_r1 base_edit_R1.fastq.gz \
--amplicon_seq AMPLICON \
--guide_seq GUIDE \
--base_editor_output \
--conversion_nuc_from C \
--conversion_nuc_to T \
--output_folder base_edit_output
```
## Prime Editing Analysis
```bash
# For prime editing
CRISPResso \
--fastq_r1 prime_edit_R1.fastq.gz \
--amplicon_seq AMPLICON \
--guide_seq GUIDE \
--prime_editing_pegRNA_spacer_seq SPACER \
--prime_editing_pegRNA_extension_seq EXTENSION \
--prime_editing_pegRNA_scaffold_seq SCAFFOLD \
--output_folder prime_edit_output
```
## Compare Samples
```bash
# Compare two CRISPResso runs
CRISPRessoCompare \
--crispresso_output_folder_1 sample1_output \
--crispresso_output_folder_2 sample2_output \
--output_folder comparison_output
```
## Related Skills
- screen-qc - QC for editing experiments
- read-alignment/bwa-alignment - Align reads for WGS analysis
- variant-calling/variant-calling - Detect editing-induced variants