Release v1.0.4

Second release of Oncodrive3D, a fast and accurate 3D-clustering algorithm for driver gene discovery. It identifies mutation-enriched volumes by analyzing missense somatic mutations, leveraging AlphaFold's structural predictions to define residue contacts and mutation profiles to simulate neutral mutagenesis. The tool uses rank-based statistics and can process mutations from duplex sequencing studies, enabling the analysis of both cancer and normal tissue datasets across potentially any organism.

Key Updates and Features

This release mainly update the README with important information and fix a bug in the oncodrive3d build-datasets step.

Documentation Updates

• General improved documentation for clarity and usability.
• Added steps to fulfill software requirements, addressing installation failures on older machines lacking updated C libraries.
• Provided detailed information on input and output data formats, including:
  • How to obtain the required input files.
  • In-depth descriptions of the main outputs, including gene-level and residue-level clustering results.

Bug Fixes and Refactoring

• Fixed bug in scripts/datasets/build_datasets.py and scripts/datasets/seq_for_mut_prob.py:
  • Disabled downloading and integrating MANE structures if --mane flag is not enabled.
  • Removed usage of files related to the MANE downloads when computing the seq_for_mut_prob.py for a non-MANE Human proteome.
• Updated scripts/datasets/utils.py to increase the timeout for sock_read in PyPdl, preventing errors during the download of AlphaFold structures.
• Refactored scripts/main.py by moving the import of specific modules into their corresponding functions for better modularity and efficiency.