aeon
Aeon is a scikit-learn compatible Python toolkit for time series machine learning. It provides state-of-the-art algorithms for classificatio…
Maintainer FreedomIntelligence · Last updated April 1, 2026
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.
Original source
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-crispr-screens-base-editing-analysis
Skill Snapshot
Source Doc
Goal: Quantify base editing efficiency and bystander edits from amplicon sequencing.
Approach: Run CRISPResso with --base_editor_output and the expected edited amplicon sequence to measure target base conversion, bystander edits, and indel frequencies.
## Key Metrics
| 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
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