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Update cas9on.py (#4)
Browse files- Update cas9on.py (bf083c28f7799d4200a4b99c657ad0f124e70a49)
Co-authored-by: Qingyang Liu <LfOreVEr@users.noreply.huggingface.co>
cas9on.py
CHANGED
@@ -70,20 +70,24 @@ def fetch_ensembl_sequence(transcript_id):
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print(f"Error fetching sequence data from Ensembl: {response.text}")
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return None
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def find_crispr_targets(sequence, chr, start, strand, transcript_id, exon_id, pam="NGG", target_length=20):
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targets = []
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len_sequence = len(sequence)
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complement = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}
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dnatorna = {'A': 'A', 'T': 'U', 'C': 'C', 'G': 'G'}
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if strand == -1:
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sequence = ''.join([complement[base] for base in sequence])
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for i in range(len_sequence - len(pam) + 1):
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if sequence[i + 1:i + 3] == pam[1:]:
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if i >= target_length:
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target_seq = sequence[i - target_length:i + 3]
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gRNA = ''.join([dnatorna[base] for base in sequence[i - target_length:i]])
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targets.append([target_seq, gRNA, chr, str(tar_start), str(tar_end), str(strand), transcript_id, exon_id])
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@@ -131,9 +135,10 @@ def process_gene(gene_symbol, model_path):
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if gene_sequence:
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all_gene_sequences.append(gene_sequence) # Add this gene sequence to the list
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start = exon['start']
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strand = exon['strand']
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chr = exon['seq_region_name']
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targets = find_crispr_targets(gene_sequence, chr, start, strand, transcript_id, exon_id)
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if targets:
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# Predict on-target efficiency for each gRNA site
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formatted_data = format_prediction_output(targets, model_path)
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print(f"Error fetching sequence data from Ensembl: {response.text}")
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return None
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+
def find_crispr_targets(sequence, chr, start, end, strand, transcript_id, exon_id, pam="NGG", target_length=20):
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targets = []
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len_sequence = len(sequence)
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#complement = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C'}
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dnatorna = {'A': 'A', 'T': 'U', 'C': 'C', 'G': 'G'}
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for i in range(len_sequence - len(pam) + 1):
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if sequence[i + 1:i + 3] == pam[1:]:
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if i >= target_length:
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target_seq = sequence[i - target_length:i + 3]
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if strand == -1:
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tar_start = end - (i + 2)
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tar_end = end - (i - target_length)
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#seq_in_ref = ''.join([complement[base] for base in target_seq])[::-1]
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else:
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tar_start = start + i - target_length
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tar_end = start + i + 3 - 1
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#seq_in_ref = target_seq
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gRNA = ''.join([dnatorna[base] for base in sequence[i - target_length:i]])
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targets.append([target_seq, gRNA, chr, str(tar_start), str(tar_end), str(strand), transcript_id, exon_id])
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if gene_sequence:
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all_gene_sequences.append(gene_sequence) # Add this gene sequence to the list
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start = exon['start']
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end = exon['end']
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strand = exon['strand']
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chr = exon['seq_region_name']
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targets = find_crispr_targets(gene_sequence, chr, start, end, strand, transcript_id, exon_id)
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if targets:
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# Predict on-target efficiency for each gRNA site
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formatted_data = format_prediction_output(targets, model_path)
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