magestic 2.0.0

Multiplexed CRISPR library design and analysis for functional genomics

MAGESTIC

Multiplexed Accurate Genome Editing with Short, Trackable, Integrated Cellular barcodes

Tools and pipelines for CRISPR-based genome editing in yeast.

Contents

Guide-Donor Oligo Design

Scripts for designing MAGESTIC guide-donor oligonucleotides:

• generate_guide_donor_oligos_for_natural_variants_from_vcf.py - Design oligos for natural variants from VCF
• generate_amino_acid_variant_guide_donor_oligos_for_saturation_editing.py - Design oligos for saturation mutagenesis
• guide_donor_oligo_functions.py - Shared functions for oligo design

Data Processing

• process_batch_editing_data.py - Process batch editing experiments
• process_overlapping_reads.sh - Handle overlapping paired-end reads
• collapse_identical_merged_reads_min_counts.py - Collapse duplicate reads

Genome Utilities

• GTF_GFF_manipulation.py - GFF/GTF file parsing and manipulation
• bedgraph_computation.py - Generate bedgraph coverage files

Variant Effect Prediction (VEP)

The VEP pipeline for running variant effect prediction models is maintained in a separate private repository.

Access: Contact Kevin Roy ([e-mail]) for access to the VEP-pipeline repository.

Supported models:

• Evo2 7B/40B - DNA sequence log-probability scores
• Yorzoi - RNA expression predictions from DNA
• Shorkie - RNA expression (8-fold ensemble)
• ESM1-v - Protein variant effect scores

Requirements

• Python 3.8+
• Biopython
• pandas, numpy
• samtools (for FASTA indexing)

Citation

If you use MAGESTIC, please cite:

Roy KR, et al. (2018). Multiplexed precision genome editing with trackable genomic barcodes in yeast. Nature Biotechnology 36:512-520.

License

MIT License - see individual files for details.