RosettaPy 0.2.0rc139.post1

A Python utility for wrapping Rosetta command line tools.

RosettaPy

A Python utility for wrapping Rosetta command line tools.

CI Status

Quality

Release

Python version supported

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:

0. PATH, which is commonly used in dockerized Rosetta image.
1. The path specified in the ROSETTA_BIN environment variable.
2. ROSETTA3/bin
3. ROSETTA/main/source/bin/
4. 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