DAS BIOTOOLS

"The great and terrifying successor of biopython"

Das biotools is a homework project made during studies in Bioinformatics institute by Michil Trofimov in September 2023.

It is a python library which is able to perform several procedures on DNA/RNA, protein sequences, filter through FASTQ data, convert multi-line FASTA to single-line FASTA and extract features from .gbk file.

Installation

git clone git@github.com:michtrofimov/das_biotools.git

cd das_biotools

Features

Tools for nucleotide sequences and aminoacids sequences support upper and lower cases.

Tools for nucleotide sequences

• check_if_procedure(procedure: str) -> None: Checks if the specified procedure is supported. Raises a ValueError if the procedure is not supported.

• check_if_empty(seqs: list) -> None: Checks if the input sequence list is empty. Raises a ValueError if the input is empty.

• filter_seqs(seqs: list, dna_alphabet: str = "ATGC", rna_alphabet: str = "AUGC") -> list: Filters out sequences that are not nucleotide sequences. Returns a list of filtered nucleotide sequences.

• transcribe(seq: str) -> str: Transcribes a DNA sequence into an RNA sequence.

• reverse_seq(seq: str) -> str: Reverses a sequence.

• complement(seq: str) -> str: Generates the complement of a nucleotide sequence, considering it as either DNA or RNA.

• reverse_complement(seq: str) -> str: Generates the reverse complement of a nucleotide sequence, considering it as either DNA or RNA.

• dna_rna_tools(*seqs: str, procedure: str) -> str: Executes a specified procedure on a list of DNA/RNA sequences. The supported procedures are "transcribe," "reverse," "complement," and "reverse_complement."

Usage

• transcribe

dna_rna_tools('ATCG', procedure='transcribe') -> "AUCG"

• reverse_seq

dna_rna_tools('ATCG', procedure='reverse') -> "GCTA"

• complement

dna_rna_tools('ATCG', procedure='complement') -> "TAGC"

• reverse_complement

dna_rna_tools('ATCG', procedure='reverse_complement') -> "CGAT"

Tools for aminoacid sequences

• is_protein(seq: str) -> bool: Check if a given sequence is a valid protein sequence.

• get_pI(sequence: str, pI_values: dict = None) -> str: Gives isoelectric point value for each aminoacid individually. User can pass their own pI values

• build_scoring_matrix(match_score: int, mismatch_score: int, amino_acid_alphabet: str = None) -> dict: Auxiliary function for needleman_wunsch. Build a scoring matrix for amino acid pairs, which can be used in sequence alignment algorithms.

• needleman_wunsch(seq1: str, seq2: str, scoring_matrix: dict = None, gap_penalty: int = -1, match_score: int = 1, mismatch_score: int = -1) -> str: Implement the Needleman-Wunsch algorithm for global sequence alignment of two amino acid sequences.

• calculate_aa_freq(sequences: str) -> dict: Calculate the frequences of aminoacids in protein sequences.

• convert_to_3L_code(seq: str) -> str: Converts one letter animoacid sequence to three letter aminoacid sequence.

• protein_mass(seq: str) -> float: Calculates molecular weight of the aminoacid sequence using monoisotopic masses.

• translate_protein_rna(seq: str) -> str: Converts aminoacid sequence to RNA sequence. For those aminoacids that are coded with more than one codon, this function randomly chooses one codon from the set.

• protein_tools(*args: any, **kwargs: any) -> any: Performs various actions on protein sequences.

  • *args: Variable number of arguments. The first one or two arguments should be protein sequences
  • **kwargs: Keyword argumets. First one is procedure, other are additional arguments for specific functions
  • The supported procedures "get_pI", "needleman_wunsch", "build_scoring_matrix", "calculate_aa_freq", "translate_protein_rna", "convert_to_3L_code", "protein_mass"

Usage

• get_pI

protein_tools('rh', pI_values = {'R' : 4,'H' : 3.5}, procedure='get_pI') -> "Sequence: rh. Isoelectric point of each aminoacid: [('r', 4), ('h', 3.5)]:

• build_scoring_matrix

protein_tools('2', '3', procedure='build_scoring_matrix') -> {'A': {'A': 2, 'C': 3, 'D': 3, ...}, 'C': {'A': 3, 'C': 2, 'D': 3, ...}, ...}

• needleman_wunsch

protein_tools('rh','rhqcqq',procedure='needleman_wunsch', gap_penalty = -2, match_score = 2) -> '----rh, rhqcqq, final score: -2'

• calculate_aa_freq

protein_tools('RAAH', procedure='calculate_aa_freq') -> {'R': 1, 'A': 2, 'H': 1}

• convert_to_3L_code

protein_tools('RAAH', procedure='convert_to_3L_code') -> "ArgAlaAlaHis"

• protein_mass

protein_tools('RAAH', procedure='protein_mass') -> 380.4934

• translate_protein_rna

protein_tools('RAAH', procedure='translate_protein_rna') -> "GACGACGACAUGAC"

Tools for FASTQ data filtering

• calculate_gc_content(seq: str) -> float: Calculates the GC content percentage of a DNA sequence.

• is_acceptable_gc(seq: str, gc_bounds: tuple) -> bool: Checks if the GC content of a DNA sequence is within specified bounds.

• is_acceptable_length(seq: str, length_bounds: tuple) -> bool: Checks if the length of a sequence falls within specified bounds.

• is_acceptable_quality_score(seq: str, quality_threshold: int) -> bool: Checks if the average quality score of a sequence is above a specified threshold.

• fastq_filter(seqs: dict, gc_bounds: tuple = (0, 100), length_bounds: tuple = (0, 2**32), quality_threshold: int = 0) -> dict: Filters a dictionary of sequences based on specified criteria. Returns a filtered dictionary containing only the sequences that meet the specified criteria.

Usage

• calculate_gc_content

fastq_filter({'read1': ('ATCG', '!!@#'), 'read2': ('GCTA', '$$%&'), 'read3': ('AAAA', '%%%%')}, gc_bounds=(40, 60)) -> {'read1': ('ATCG', '!!@#'), 'read2': ('GCTA', '$$%&')}

• is_acceptable_length

fastq_filter({'read1': ('ATCG', '!!@#'), 'read2': ('GCTA', '$$%&'), 'read3': ('AAAA', '%%%%')}, length_bounds=(2, 4)) -> {'read1': ('ATCG', '!!@#'), 'read3': ('AAAA', '%%%%')}

• is_acceptable_quality_score

fastq_filter({'read1': ('ATCG', '!!@#'), 'read2': ('GCTA', '$$%&'), 'read3': ('AAAA', '%%%%')}, quality_threshold=10) -> {'read1': ('ATCG', '!!@#'), 'read2': ('GCTA', '$$%&'), 'read3': ('AAAA', '%%%%')}

Tools for bio-files processing

• convert_multiline_fasta_to_oneline(input_fasta: str, output_fasta: str = None): Convert a multi-line FASTA file to a one-line FASTA file.

• def select_genes_from_gbk_to_fasta( input_gbk: str, genes: List[str], n_before: int = 1, n_after: int = 1, output_fasta: str = None, ):: Extracts gene sequences from a GenBank (gbk) file and creates a FASTA file with specified neighboring genes.

Usage

• convert_multiline_fasta_to_oneline

convert_multiline_fasta_to_oneline('example_multiline_fasta.fasta') -> "example_multiline_fasta_converted.fasta"

• select_genes_from_gbk_to_fasta

select_genes_from_gbk_to_fasta('example_gbk.gbk', 'flu_2', n_before = 2, n_after = 3) -> "example_gbk_flanking_genes.fasta"