Biopython Bioinformatics Best Practice

Sequence Manipulation

1. Create sequences: from Bio.Seq import Seq; seq = Seq("ATGCGA")
2. Complement: seq.complement(); Reverse complement: seq.reverse_complement()
3. Transcription: seq.transcribe() (DNA to RNA)
4. Translation: seq.translate() (DNA/RNA to protein)
5. GC content: from Bio.SeqUtils import gc_fraction; gc_fraction(seq)
6. Molecular weight: from Bio.SeqUtils import molecular_weight

File Parsing (SeqIO)

1. Read FASTA: for rec in SeqIO.parse("file.fasta", "fasta"): ...
2. Read GenBank: for rec in SeqIO.parse("file.gb", "genbank"): ...
3. Read single record: rec = SeqIO.read("file.fasta", "fasta")
4. Write sequences: SeqIO.write(records, "output.fasta", "fasta")
5. Convert formats: SeqIO.convert("input.gb", "genbank", "output.fasta", "fasta")
6. Index large files: idx = SeqIO.index("large.fasta", "fasta") for random access

BLAST Operations

1. Online BLAST: from Bio.Blast import NCBIWWW; result = NCBIWWW.qblast("blastn", "nt", seq)
2. Parse results: from Bio.Blast import NCBIXML; records = NCBIXML.parse(result)
3. Local BLAST: run via subprocess, parse XML output with NCBIXML
4. Always set Entrez.email before any NCBI access
5. Filter results by e-value (typically < 1e-5) and coverage

NCBI Database Access (Entrez)

1. Always set email: Entrez.email = "your@email.com"
2. Search: handle = Entrez.esearch(db="pubmed", term="query")
3. Fetch records: handle = Entrez.efetch(db="nucleotide", id="ID", rettype="fasta")
4. Use API key for higher rate limits (10 req/s vs 3 req/s)
5. Respect NCBI rate limits; add delays between batch requests

Phylogenetics (Bio.Phylo)

1. Read trees: from Bio import Phylo; tree = Phylo.read("tree.nwk", "newick")
2. Draw trees: Phylo.draw(tree) or Phylo.draw_ascii(tree)
3. Supported formats: newick, nexus, phyloxml
4. Traverse clades: for clade in tree.find_clades(): ...
5. Calculate distances: tree.distance(clade1, clade2)

Structure Analysis (Bio.PDB)

1. Parse PDB: parser = PDBParser(); structure = parser.get_structure("id", "file.pdb")
2. Hierarchy: Structure > Model > Chain > Residue > Atom
3. Get atoms: iterate through structure.get_atoms()
4. Calculate distances: use atom coordinate vectors
5. For mmCIF files: use MMCIFParser() instead of PDBParser()

Common Pitfalls

1. Always handle SeqIO.parse as an iterator — it exhausts after one pass
2. Check sequence alphabet compatibility before operations
3. Large files: use SeqIO.index() not SeqIO.to_dict() to avoid memory issues
4. Set proper timeout for remote BLAST queries (can take minutes)
5. Validate parsed data — missing annotations are common in public databases