Pre-release v1.0.1-rc

This is the first pre-release of Oncodrive3D, a fast and accurate novel 3D-clustering algorithm for driver genes discovery. This approach involves analysing patterns of observed missense somatic mutations (in cancer or normal tissue) to identify volumes that exhibit a higher-than-expected frequency of mutations than what is typically observed under neutral mutagenesis. Oncodrive3D leverages AlphaFold's structure predictions and Predicted Aligned Error (PAE) to construct contact probability maps. Moreover, if provided, it uses the mutation profile of the cohort to simulate neutral mutagenesis while employing rank-based statistics to determine empirical p-values for the volumes of each mutated residue. Also, It can process the mutation profile and sequencing depth information. If provided as a mutability file, this allows the tool to process mutations obtained from duplex sequencing studies, which are commonly used in normal tissue sequencing at the time of this release.

Input

• input.maf (required): Mutation Annotation Format (MAF) file annotated with consequences (e.g., by using Ensembl Variant Effect Predictor (VEP)).

• mut_profile.json (optional): Dictionary including the normalized frequencies of mutations (values) in every possible trinucleotide context (keys), such as 'ACA>A', 'ACC>A', and so on.

• mut_config.json (optional): Dictionary including the path and parsing information for the mutability file, which includes information about mutation profile integrated with sequencing depth.

Output

• cohort_filename.3d_clustering_genes.csv: This is a Comma-Separated Values (CSV) file containing the results of the analysis at the gene level.

• cohort_filename.3d_clustering_pos.csv: This is a Comma-Separated Values (CSV) file containing the results of the analysis at the level of mutated positions.