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Make sure you have have Conda installed on your computer.
conda env create -n guido -f requirements.txt
After creating the environment you can activate it by using:
conda activate guido
To get out of the environment use:
conda deactivate
pip install -r requirements.txt
Download ZIP from: https://imperialcollegelondon.box.com/v/guido-agam-data and extract the archive into guido/ folder.
usage: guido.py [-h] [--sequence-file SEQUENCE] [--region REGION]
[--gene GENE] [--variants VARIANTS]
[--feature-type FEATURE_TYPE] [--pam PAM]
[--max-flanking MAX_FLANKING_LENGTH]
[--min-flanking MIN_FLANKING_LENGTH]
[--length-weight LENGTH_WEIGHT] [--n-patterns N_PATTERNS]
[--output-folder OUTPUT_FOLDER]
optional arguments:
-h, --help show this help message and exit
--sequence-file SEQUENCE, -i SEQUENCE
File with the target sequence (TXT or FASTA).
--region REGION, -r REGION
Region in AgamP4 genome [2L:1530-1590].
--gene GENE, -G GENE Genome of interest (AgamP4.7 geneset).
--variants VARIANTS, -v VARIANTS
VCF file with variants.
--feature-type FEATURE_TYPE, -f FEATURE_TYPE
Genomic feature to target.
--pam PAM, -P PAM Protospacer Adjacent Motif (IUPAC code format).
--max-flanking MAX_FLANKING_LENGTH, -M MAX_FLANKING_LENGTH
Max length of flanking region.
--min-flanking MIN_FLANKING_LENGTH, -m MIN_FLANKING_LENGTH
Min length of flanking region.
--length-weight LENGTH_WEIGHT, -w LENGTH_WEIGHT
Length weight - used in scoring.
--n-patterns N_PATTERNS, -p N_PATTERNS
Number of MH patterns used in guide evaluation.
--output-folder OUTPUT_FOLDER, -o OUTPUT_FOLDER
Output folder.
guide_sequence genomic_location exon_name strand off_target_analysis MMEJ_score MMEJ_sum_score MMEJ_top_score SNP_count wt_prob SNP_info MMEJ_out_of_frame_del
GGAGCAGTTCAGCAGCGCGGCGG X:1300558-1300580 AGAP000080-RD-E7 - [0, 0, 0, 1] 100.0 2082.9 634.7 1 0.9762 1300563:G/[T]([0.0238]) + + + + +
GCTGCCGCTGCCCGGAGAGACGG X:1300426-1300449 AGAP000080-RD-E7 + [0, 0, 0, 0] 100.0 1649.2 603.0 0 1.0 + + + + +
GGTTGCCGCCTCCGTCTCTCCGG X:1300438-1300460 AGAP000080-RD-E7 - [0, 0, 0, 0] 100.0 1649.2 603.0 0 1.0 + + + + +
GTTGCCGCCTCCGTCTCTCCGGG X:1300437-1300459 AGAP000080-RD-E7 - [0, 0, 0, 0] 100.0 1515.2 469.0 0 1.0 + + + + +
GTTCGGAATGGGAGGGAAGTCGG X:1300498-1300521 AGAP000080-RD-E7 + [0, 0, 0, 1] 100.0 1484.3 352.5 0 1.0 + + + + +
CTGACCTTTGAACGGCTCTCAGG X:1300905-1300927 AGAP000080-RD-E7 - [0, 0, 0, 0] 100.0 1436.9 402.0 0 1.0 + + + + +
GCCTCCGTCTCTCCGGGCAGCGG X:1300431-1300453 AGAP000080-RD-E7 - [0, 0, 0, 0] 100.0 1409.4 423.0 0 1.0 + + + + +
GGGCTTGAAGCTGCTGTTTGCGG X:1300621-1300644 AGAP000080-RD-E7 + [0, 0, 0, 0] 100.0 1383.5 352.5 0 1.0 + + + + +
ACCTTTGAACGGCTCTCAGGCGG X:1300902-1300924 AGAP000080-RD-E7 - [0, 0, 0, 0] 100.0 1355.6 402.0 0 1.0 + + + + +
CGCTTCTGGTGTAGGTCGCCCGG X:1300779-1300802 AGAP000080-RD-E7 + [0, 0, 0, 0] 100.0 1019.5 268.0 0 1.0 + + + + +
Guide: GGAGCAGTTCAGCAGCGCGGCGG Location: X:1300558-1300580 Strand: -
MMEJ score: 100.0 MMEJ sum score: 2082.9 MMEJ top score: 634.7
Top MMEJ patterns
Pattern Score Deletion size Produces out-of-frame deletion MH seq Deletion seq
GCGGTCGCGAACAGCTTCAAGTCGGAGCAGTTCA------+++++GCAGCGGTTGCCAATTACGCGCTCGGGACCTTCAA 634.7 11 + GCAGCG GCAGCGCGGCG
GCGGTCGCGAACAGCTTCAAGTCGGAGCAGTTCAGCA---++GCGGCAGCGGTTGCCAATTACGCGCTCGGGACCTTCAA 467.4 5 + GCG GCGCG
GCGGTCGCGAACAGCTTCAAGTCGGAGCAGTTCAGCAG--CGGCGGCAGCGGTTGCCAATTACGCGCTCGGGACCTTCAA 362.0 2 + CG CG
GCGGTCGCGAACAGCTTCAAGTCGGAGCAGTT--------++++++CAGCGGTTGCCAATTACGCGCTCGGGACCTTCAA 347.9 14 + CAGC CAGCAGCGCGGCGG
GCGGTCGCGAACAGCTTCAAGTCGGA--------------+++++GCAGCGGTTGCCAATTACGCGCTCGGGACCTTCAA 270.9 19 + GCAG GCAGTTCAGCAGCGCGGCG
Variants
Position Ref/Alt Frequency
1300563 G/[T] 0.0238
WT allele probability: 0.9762
Off-targets
Number off-targets with
[0, 1, 2, 3] mismatches
[0, 0, 0, 1]
Chromosome Start position Strand Mismatches
2L:33877342 + 1: T>G, 2: T>A, 15: G>C