name: bio-crispr-screens-base-editing-analysis description: Analyzes base editing and prime editing outcomes including editing efficiency, bystander edits, and indel frequencies. Use when quantifying CRISPR base editor results, comparing ABE vs CBE efficiency, or assessing prime editing fidelity. tool_type: python primary_tool: CRISPResso2

Base Editing Analysis

CRISPResso2 for Base Editing

# Analyze base editing with expected outcome
CRISPResso --fastq_r1 reads.fq.gz \
    --amplicon_seq ATGCGATCGATCGATCGATCGATCG \
    --guide_seq TCGATCGATCGATCGAT \
    --expected_hdr_amplicon_seq ATGCGATCGATCGTTCGATCGATCG \
    --base_editor_output \
    -o results/

Key Metrics

Base Editor Types

Cytosine Base Editors (CBE)

# C->T conversion (or G->A on opposite strand)
CRISPResso --fastq_r1 reads.fq.gz \
    --amplicon_seq $AMPLICON \
    --guide_seq $GUIDE \
    --base_editor_output \
    --conversion_nuc_from C \
    --conversion_nuc_to T

Adenine Base Editors (ABE)

# A->G conversion (or T->C on opposite strand)
CRISPResso --fastq_r1 reads.fq.gz \
    --amplicon_seq $AMPLICON \
    --guide_seq $GUIDE \
    --base_editor_output \
    --conversion_nuc_from A \
    --conversion_nuc_to G

Prime Editing Analysis

# Prime editing with pegRNA
CRISPResso --fastq_r1 reads.fq.gz \
    --amplicon_seq $AMPLICON \
    --guide_seq $SPACER \
    --expected_hdr_amplicon_seq $EDITED_AMPLICON \
    --prime_editing_pegRNA_extension_seq $EXTENSION \
    -o prime_edit_results/

Editing Window Analysis

import pandas as pd

# Load CRISPResso quantification
quant = pd.read_csv('CRISPResso_output/Quantification_window_nucleotide_percentage_table.txt',
                    sep='\t')

# Calculate per-position editing
editing_window = quant[(quant['Position'] >= -5) & (quant['Position'] <= 5)]

Quality Thresholds

• Editing efficiency: >30% considered good for most applications
• Indel rate: <5% ideal for base editors
• Bystander rate: depends on application; <10% often acceptable

Related Skills

• crispr-screens/crispresso-editing - General editing QC
• crispr-screens/library-design - Guide design considerations
• variant-calling/vcf-basics - Downstream variant analysis