Biotite project
Biotite is your Swiss army knife for bioinformatics. Whether you want to identify homologous sequence regions in a protein family or you would like to find disulfide bonds in a protein structure: Biotite has the right tool for you. This package bundles popular tasks in computational molecular biology into a uniform Python library. It can handle a major part of the typical workflow for sequence and biomolecular structure data:
- Searching and fetching data from biological databases
- Reading and writing popular sequence/structure file formats
- Analyzing and editing sequence/structure data
- Visualizing sequence/structure data
- Interfacing external applications for further analysis
Biotite internally stores most of the data as NumPy ndarray objects, enabling
- fast C-accelerated analysis,
- intuitive usability through NumPy-like indexing syntax,
- extensibility through direct access of the internal NumPy arrays.
As a result the user can skip writing code for basic functionality (like file parsers) and can focus on what their code makes unique - from small analysis scripts to entire bioinformatics software packages.
If you use Biotite in a scientific publication, please cite:
Installation
Biotite requires the following packages:
- numpy
- requests
- msgpack
- networkx
Some functions require some extra packages:
- mdtraj - Required for trajetory file I/O operations.
- matplotlib - Required for plotting purposes.
Biotite can be installed via Conda...
$ conda install -c conda-forge biotite... or pip
$ pip install biotiteUsage
Here is a small example that downloads two protein sequences from the NCBI Entrez database and aligns them:
import biotite.sequence.align as align
import biotite.sequence.io.fasta as fasta
import biotite.database.entrez as entrez
# Download FASTA file for the sequences of avidin and streptavidin
file_name = entrez.fetch_single_file(
uids=["CAC34569", "ACL82594"], file_name="sequences.fasta",
db_name="protein", ret_type="fasta"
)
# Parse the downloaded FASTA file
# and create 'ProteinSequence' objects from it
fasta_file = fasta.FastaFile.read(file_name)
avidin_seq, streptavidin_seq = fasta.get_sequences(fasta_file).values()
# Align sequences using the BLOSUM62 matrix with affine gap penalty
matrix = align.SubstitutionMatrix.std_protein_matrix()
alignments = align.align_optimal(
avidin_seq, streptavidin_seq, matrix,
gap_penalty=(-10, -1), terminal_penalty=False
)
print(alignments[0])MVHATSPLLLLLLLSLALVAPGLSAR------KCSLTGKWDNDLGSNMTIGAVNSKGEFTGTYTTAV-TA -------------------DPSKESKAQAAVAEAGITGTWYNQLGSTFIVTA-NPDGSLTGTYESAVGNA TSNEIKESPLHGTQNTINKRTQPTFGFTVNWKFS----ESTTVFTGQCFIDRNGKEV-LKTMWLLRSSVN ESRYVLTGRYDSTPATDGSGT--ALGWTVAWKNNYRNAHSATTWSGQYV---GGAEARINTQWLLTSGTT DIGDDWKATRVGINIFTRLRTQKE--------------------- -AANAWKSTLVGHDTFTKVKPSAASIDAAKKAGVNNGNPLDAVQQ
More documentation, including a tutorial, an example gallery and the API reference is available at https://www.biotite-python.org/.
Contribution
Interested in improving Biotite? Have a look at the contribution guidelines. Feel free to join or community chat on Discord.