xiaohongshu
xiaohongshu
bio-crispr-screens-base-editing-analysis
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.
Full skill instructions
# 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/
| Metric | Description |
|---|---|
| Editing efficiency | % reads with target base change |
| Bystander edits | Unintended edits in editing window |
| Indel frequency | Insertions/deletions (should be low) |
| Purity | Target edit without bystanders |
# 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
# 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 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/
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)]
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