Completed HW6_Files

BioSeqTools.py

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+from Modules.filter_fastq import run_filter_fastq
+from Modules.dna_rna_tools import run_dna_rna_tools
+from Modules.aminoacids_tools import run_aminoacid_tools
+
+def run_BioSeqTools(tool_name, *args):
+    if tool_name == "run_aminoacid_tools":
+        if len(args) < 2:
+            raise ValueError("Not enough arguments for run_aminoacid_tools")
+        return run_aminoacid_tools(*args[:-1], operation=args[-1])
+    elif tool_name == "run_dna_rna_tools":
+        return run_dna_rna_tools(*args)
+    elif tool_name == "run_filter_fastq":
+        return run_filter_fastq(*args)
+    else:
+        raise ValueError("Invalid tool_name")

Modules/aminoacids_tools.py

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+from typing import Dict
+
+
+def calculate_percentage(seq: str) -> str:
+    """
+    Calculates the percentage of amino acids in the entered amino acid 
+sequence
+    Arguments:
+        - seq (str): amino acid sequences to be analyzed
+    Return:
+        - str: a string with the percentage of each amino acid
+    """
+    amino_acid_counts: Dict[str, int] = {}  # dict to store count of each amino acid
+    for amino_acid in seq:
+        if amino_acid in amino_acid_counts:
+            amino_acid_counts[amino_acid] += 1
+        else:
+            amino_acid_counts[amino_acid] = 1
+    total_amino_acids = len(seq)
+    amino_acid_percentages = {}  # dict to store each amino acid and its %
+    for amino_acid, count in amino_acid_counts.items():
+        percentage = round(((count / total_amino_acids) * 100), 2)
+        amino_acid_percentages[amino_acid] = percentage
+    return f'Amino acids percentage of the sequence {seq}: {amino_acid_percentages}'
+
+
+def calculate_molecular_weight(seq: str) -> str:
+    """
+    Calculates the molecular weight of entered amino acid sequence
+    Arguments:
+        - seq (str): amino acid sequences to be analyzed
+    Return:
+        - str: a string with the molecular weight value for amino acid 
+sequence
+    """
+    amino_acid_weights = {
+        'G': 57.051, 'A': 71.078, 'S': 87.077, 'P': 97.115, 'V': 99.131,
+        'T': 101.104, 'C': 103.143, 'I': 113.158, 'L': 113.158, 'N': 
+114.103,
+        'D': 115.087, 'Q': 128.129, 'K': 128.172, 'E': 129.114, 'M': 
+131.196,
+        'H': 137.139, 'F': 147.174, 'R': 156.186, 'Y': 163.173, 'W': 
+186.210
+    }
+    weight = 18.02  # for the H and OH at the termini
+    for amino_acid in seq:
+        weight += amino_acid_weights[amino_acid]
+    return f'Molecular weight of the sequence {seq}: {round(weight, 2)} Da'
+
+
+def calculate_hydrophobicity_eisenberg(sequence):
+
+    # Amino acid hydrophilicity/hydrophobicity scale by Eisengerg
+    hydrophobicity_values = {
+        'A': 0.5, 'R': 0.65, 'N': 1.0, 'D': 1.3, 'C': -0.15,
+        'Q': 1.0, 'E': 1.5, 'G': 0.75, 'H': 0.7, 'I': -1.3,
+        'L': -1.3, 'K': 0.75, 'M': -1.1, 'F': -1.9, 'P': 0.55,
+        'S': 0.6, 'T': 0.3, 'W': -0.5, 'Y': -1.65, 'V': -0.9
+    }
+
+    # Calculate sum of hydrophilicities for all amino acids in the sequence
+    hydrophobicity_sum = sum(hydrophobicity_values.get(aa, 0) for aa in sequence)
+
+    # Determine hydrophilicity/hydrophobicity of sequence
+    if hydrophobicity_sum > 0:
+        return f"Sequence {sequence}: Hydrophilic"
+    elif hydrophobicity_sum < 0:
+        return f"Sequence {sequence}: Hydrophobic"
+    else:
+        return f"Sequence {sequence}: Neutral"
+
+
+def calculate_pI(sequence):
+    """Create a dictionary of pK values (COO-, NH3+, R) information taken
+    from source 
+http://www.sev-chem.narod.ru/spravochnik/piaminoacid.htm"""
+    pK_values = {
+        'A': (2.34, 9.60),
+        'R': (2.17, 9.04, 12.48),
+        'N': (2.02, 8.80),
+        'D': (2.09, 9.82, 3.86),
+        'C': (1.71, 8.33, 10.30),
+        'Q': (2.17, 9.13),
+        'E': (2.19, 9.76, 4.25),
+        'G': (2.34, 9.60),
+        'H': (1.82, 9.17, 6.00),
+        'I': (2.32, 9.76),
+        'L': (2.36, 9.60),
+        'K': (2.18, 8.95, 10.5),
+        'M': (2.28, 9.21),
+        'F': (2.58, 9.24),
+        'P': (2.00, 10.60),
+        'S': (2.21, 9.15),
+        'T': (2.63, 10.43),
+        'W': (1.22, 9.39),
+        'Y': (2.20, 9.11, 10.10),
+        'V': (2.29, 9.72)
+    }
+
+    # Initialization of variables for leftmost and rightmost elements
+    N_end_pK = None
+    C_end_pK = None
+
+    # Find the marginal elements and their corresponding pKs
+    for amino_acid in sequence:
+        if amino_acid in pK_values:
+            pK_list = pK_values[amino_acid]
+            if len(pK_list) >= 2:
+                if N_end_pK is None:
+                    N_end_pK = pK_list[1]  # Второй pK
+                C_end_pK = pK_list[0]  # Первый pK
+
+    # If no amino acid sequence is specified - return None
+    if N_end_pK is None or C_end_pK is None:
+        return None
+
+    # Calculate pI
+    total_pK = N_end_pK + C_end_pK
+    count = 2  # We take into account the found pKs - there are at least 2
+
+    # Also add pK of AA radicals - the dictionary contains 3 pK values
+    for amino_acid in sequence:
+        if amino_acid in pK_values:
+            pK_list = pK_values[amino_acid]
+            if len(pK_list) >= 3:
+                total_pK += pK_list[2]  # Третий pK
+                count += 1
+
+    # Substitute all found values into the formula and calculate pI
+    pI = total_pK / count
+    return f"Isoelectric point for the sequence {sequence}: {pI}"
+
+
+def find_cleavage_sites(seq: str, motif: list) -> list:
+    """Find cleavage sites for motif-specific proteases.
+    Arguments:
+    - seq - string sequence to be analyzed
+    - motif - subsequence to be found in a sequence. Subsequence is 
+specified as list of lists.
+    Each nested list means more than one possible aminoacid at a single 
+position (checked by OR condition).
+    Return:
+    - list of cleavage sites coordinates (C-end aminoacid of *potentially* 
+cleaved sequence)
+    """
+    cleavage_sites = []
+    seq_idx = 0
+    while seq_idx < len(seq):
+        motif_idx = 0
+        chars_at_motif_idx = motif[motif_idx]
+        seq_char = seq[seq_idx]
+        if seq_char in chars_at_motif_idx:
+            motif_idx += 1
+            while motif_idx < len(motif):
+                chars_at_motif_idx = motif[motif_idx]
+                seq_char = seq[seq_idx+motif_idx]
+                if seq_char in chars_at_motif_idx:
+                    motif_idx += 1
+                else:
+                    break
+            if motif_idx == len(motif):
+                cleavage_sites.append(seq_idx + motif_idx)
+        seq_idx += 1
+    return cleavage_sites
+
+
+motif_dict = {
+    'Caspase 3': [['D'], ['M'], ['Q'], ['D']],
+    'Caspase 6': [['V'], ['E'], ['H', 'I'], ['D']],
+    'Caspase 7': [['D'], ['E'], ['V'], ['D']],
+    'Enterokinase': [['D', 'E'], ['D', 'E'], ['D', 'E'], ['K']]
+}
+
+
+def get_cleavage_sites(seq: str) -> str:
+    "Return amount and coordinates of cleavage sites for proteases, specified in motif_dict"
+    output = f'{seq}\n'
+    for motif_name, motif_value in motif_dict.items():
+        sites = find_cleavage_sites(seq, motif_value)
+        output += f'{len(sites)} protease cleavage site(s) for {motif_name}: {sites}\n'
+    return output
+
+
+all_aminoacids = {
+    'A', 'R', 'N', 'D', 'C', 'H', 'G', 'Q', 'E', 'I',
+    'L', 'K', 'M', 'P', 'S', 'Y', 'T', 'W', 'F', 'V'
+}
+
+
+def is_peptide(seq: str) -> bool:
+    "Check whether the incoming sequence is an aminoacid"
+    if set(seq).issubset(all_aminoacids):  # if set(seq) <= all_aminoacids
+        return True
+    raise ValueError(f'Incoming sequence {seq} is not a peptide')
+
+
+operation_dict = {
+    'get_cleavage_sites': get_cleavage_sites,
+    'calculate_molecular_weight': calculate_molecular_weight,
+    'calculate_percentage': calculate_percentage,
+    'calculate_pI': calculate_pI,
+    'calculate_hydrophobicity_eisenberg': 
+calculate_hydrophobicity_eisenberg
+}
+
+
+def run_aminoacid_tools(*seqs: str, operation: str) -> str:
+    """Run AminoAcid Tools
+    Arguments:
+    - *seqs - one or more string sequences to be analyzed
+    - operation - action to be done with sequence(s)
+    Return:
+    - string that contains incoming sequence and result of operation"""
+    if operation == '':
+        raise ValueError('Operation value is not specified')
+    if operation not in operation_dict:
+        raise ValueError(f'Incorrect operation value\nSupported operations: {list(operation_dict.keys())}')
+    for seq in seqs:
+        is_peptide(seq)
+    output = ''
+    for seq in seqs:
+        output += operation_dict[operation](seq)
+        output += '\n\n'
+    return output

Modules/dna_rna_tools.py

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+def transcribe(dna_sequence):
+    rna_sequence = ''
+    for base in dna_sequence:
+        if base == 'T':
+            rna_sequence += 'U'
+        elif base == 't':
+            rna_sequence += 'u'
+        elif base == 'U':
+            rna_sequence += 'T'
+        elif base == 'u':
+            rna_sequence += 't'
+        else:
+            rna_sequence += base
+    return rna_sequence
+
+def reverse(sequence):
+    return sequence[::-1]
+
+def complement(sequence):
+    complement_dict = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C', 'a': 't',
+                       't': 'a', 'c': 'g', 'g': 'c'}
+    complement_sequence = ''.join(complement_dict.get(base, base)
+                                  for base in sequence)
+    return complement_sequence
+
+def reverse_complement(dna_sequence):
+    # можно также "complement_sequence = complement(dna_sequence)"
+    complement_dict = {'A': 'T', 'T': 'A', 'C': 'G', 'G': 'C', 'a': 't',
+                       't': 'a', 'c': 'g', 'g': 'c'}
+    complement_sequence = ''.join(complement_dict.get(base, base)
+                                  for base in dna_sequence)
+    return complement_sequence[::-1]
+
+def run_dna_rna_tools(*args):
+    if not args:
+        return "There are no function arguments"
+    action = args[-1].lower()
+    sequences = args[:-1]
+    results = []
+    for sequence in sequences:
+        if not all(base in 'ACGTU' for base in sequence.upper()):
+            results.append(f"Invalid sequence: {sequence}")
+        elif action == 'transcribe':
+            results.append(transcribe(sequence))
+        elif action == 'reverse':
+            results.append(reverse(sequence))
+        elif action == 'complement':
+            results.append(complement(sequence))
+        elif action == 'reverse_complement':
+            results.append(reverse_complement(sequence))
+        else:
+            results.append(f"Invalid action: {action}")
+    return results[0] if len(results) == 1 else results

Modules/filter_fastq.py

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+def run_filter_fastq(seqs, gc_bounds=(0, 100), length_bounds=(0, 2**32), quality_threshold=0):
+    filtered_seqs = {}
+
+    for name, (sequence, quality) in seqs.items():
+        # Estimate GC-content
+        gc_content = (sequence.count('G') + sequence.count('C')) / len(sequence) * 100
+
+        # Estimate average quality
+        avg_quality = sum(ord(q) - 33 for q in quality) / len(quality)
+
+        # Filtering by user`s conditions
+        if (
+            gc_bounds[0] <= gc_content <= gc_bounds[1] and
+            length_bounds[0] <= len(sequence) <= length_bounds[1] and
+            avg_quality >= quality_threshold
+        ):
+            filtered_seqs[name] = (sequence, quality)
+
+    return filtered_seqs
+