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A Python utility for wrapping Rosetta command line tools.

Project description

RosettaPy

A Python utility for wrapping Rosetta command line tools.

License

GitHub License

CI Status

Python CI Test with Rosetta Dependabot Updates Pylint

Quality

codecov CodeFactor Maintainability Codacy Badge Pylint GitHub repo size

Release

GitHub Release GitHub Release Date

PyPI - Format PyPI - Version PyPI - Status PyPI - Wheel

Python version supported

PyPI - Python Version PyPI - Implementation

Overview

RosettaPy is a Python module designed to locate Rosetta biomolecular modeling suite binaries that follow a specific naming pattern and execute Rosetta in command line. The module includes:

Building Blocks

  • An object-oriented RosettaFinder class to search for binaries.
  • A RosettaBinary dataclass to represent the binary and its attributes.
  • A RosettaCmdTask dataclass to represent a single Rosetta run task.
  • A RosettaContainer dataclass to wrap runs into Rosetta Containers.
  • A MPI_node dataclass to manage MPI resourses. Not Seriously Tested
  • A command-line wrapper dataclass Rosetta for handling Rosetta runs.
  • A RosettaScriptsVariableGroup dataclass to represent Rosetta scripts variables.
  • A general and simplified result analyzer RosettaEnergyUnitAnalyser to read and interpret Rosetta output score files.
  • A series of example applications that follow the design elements and patterns described above.
    • PROSS
    • FastRelax
    • RosettaLigand
    • Supercharge
    • MutateRelax
    • Cartesian ddG (Analyser: RosettaCartesianddGAnalyser)
  • Unit tests to ensure reliability and correctness.

Features

  • Flexible Binary Search: Finds Rosetta binaries based on their naming convention.
  • Platform Support: Supports Linux and macOS operating systems.
  • Container Support: Works with Docker containers running upon the official Rosetta Docker image.
  • Customizable Search Paths: Allows specification of custom directories to search.
  • Structured Binary Representation: Uses a dataclass to encapsulate binary attributes.
  • Command-Line Shortcut: Provides a quick way to find binaries via the command line.
  • Available on PyPI: Installable via pip without the need to clone the repository.
  • Unit Tested: Includes tests for both classes to ensure functionality.

Naming Convention

The binaries are expected to follow this naming pattern:

rosetta_scripts[[.mode].oscompilerrelease]
  • Binary Name: rosetta_scripts (default) or specified.
  • Mode (optional): default, mpi, or static.
  • OS (optional): linux or macos.
  • Compiler (optional): gcc or clang.
  • Release (optional): release or debug.

Examples of valid binary filenames:

  • rosetta_scripts (dockerized Rosetta)
  • rosetta_scripts.linuxgccrelease
  • rosetta_scripts.mpi.macosclangdebug
  • rosetta_scripts.static.linuxgccrelease

Installation

Ensure you have Python 3.8 or higher installed.

Install via PyPI

You can install RosettaPy directly from PyPI:

pip install RosettaPy -U

Usage

Building Your Own Rosetta Workflow

# Imports
from RosettaPy import Rosetta, RosettaScriptsVariableGroup, RosettaEnergyUnitAnalyser
from RosettaPy.node import RosettaContainer

# Create a Rosetta object with the desired parameters
rosetta = Rosetta(
    bin="rosetta_scripts",
    flags=[...],
    opts=[
        "-in:file:s", os.path.abspath(pdb),
        "-parser:protocol", "/path/to/my_rosetta_scripts.xml",
    ],
    output_dir=...,
    save_all_together=True,
    job_id=...,

    # Some Rosetta Apps (Superchange, Cartesian ddG, etc.) may produce files in the working directory,
    # and this may not threadsafe if one runs multiple jobs in parallel in the same directory.
    # In this case, the `isolation` flag can be used to create a temporary directory for each run.
    # isolation=True,

    # Optionally, if one wishes to use the Rosetta container.
    # The image name can be found at https://hub.docker.com/r/rosettacommons/rosetta
    # run_node=RosettaContainer(image="rosettacommons/rosetta:latest")
)

# Compose your Rosetta tasks matrix
tasks = [ # Create tasks for each variant
    {
        "rsv": RosettaScriptsVariableGroup.from_dict(
            {
                "var1": ...,
                "var2": ...,
                "var3": ...,
            }
        ),
        "-out:file:scorefile": f"{variant}.sc",
        "-out:prefix": f"{variant}.",
    }
    for variant in variants
]

# Run Rosetta against these tasks
rosetta.run(inputs=tasks)

# Or create a distributed runs with structure labels (-nstruct)
options=[...] # Passing an optional list of options that will be used to all structure models
rosetta.run(nstruct=nstruct, inputs=options) # input options will be passed to all runs equally

# Use Analyzer to check the results
analyser = RosettaEnergyUnitAnalyser(score_file=rosetta.output_scorefile_dir)
best_hit = analyser.best_decoy
pdb_path = os.path.join(rosetta.output_pdb_dir, f'{best_hit["decoy"]}.pdb')

# Ta-da !!!
print("Analysis of the best decoy:")
print("-" * 79)
print(analyser.df.sort_values(by=analyser.score_term))

print("-" * 79)

print(f'Best Hit on this run: {best_hit["decoy"]} - {best_hit["score"]}: {pdb_path}')
#

Environment Variables

The RosettaFinder searches the following directories by default:

  1. PATH, which is commonly used in dockerized Rosetta image.
  2. The path specified in the ROSETTA_BIN environment variable.
  3. ROSETTA3/bin
  4. ROSETTA/main/source/bin/
  5. A custom search path provided during initialization.

Running Tests

The project includes unit tests using Python's pytest framework.

  1. Clone the repository (if not already done):

    git clone https://github.com/YaoYinYing/RosettaPy.git
    cd RosettaPy
    
  2. Navigate to the project directory:

    cd RosettaPy
    
  3. Run the tests:

    python -m pytest ./tests
    

Contributing

Contributions are welcome! Please submit a pull request or open an issue for bug reports and feature requests.

License

This project is licensed under the MIT License.

Acknowledgements

  • Rosetta Commons: The Rosetta software suite for the computational modeling and analysis of protein structures.

Contact

For questions or support, please contact:

  • Name: Yinying Yao
  • Email:yaoyy.hi(a)gmail.com

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