
Erika Rivarola developed and enhanced a reproducible validation workflow for subclonal deconvolution results in the caravagnalab/ProCESS-examples repository. She designed R scripts to process mutation data and integrate outputs from PyClone, Viber, and Mobster, enabling standardized cross-caller comparison and improving the reliability of subclonal inferences. Her work included upgrading the validation script, incorporating new R libraries, and refining data extraction and processing steps to support robust downstream analyses. Erika’s contributions demonstrated depth in bioinformatics, data analysis, and R programming, resulting in improved data integrity, reproducibility, and accuracy for subclonal mutation analysis within the project.

2025-07 Monthly Summary for caravagnalab/ProCESS-examples: Focused on enhancing the subclonal deconvolution validation workflow by upgrading the validation script, integrating new libraries, and refining data processing steps. The changes improve extraction and cross-tool comparison of clonal clusters, increasing reliability of mutation analysis and supporting downstream analyses. Commit reference included in this effort (see details below).
2025-07 Monthly Summary for caravagnalab/ProCESS-examples: Focused on enhancing the subclonal deconvolution validation workflow by upgrading the validation script, integrating new libraries, and refining data processing steps. The changes improve extraction and cross-tool comparison of clonal clusters, increasing reliability of mutation analysis and supporting downstream analyses. Commit reference included in this effort (see details below).
2025-06 Monthly Summary for caravagnalab/ProCESS-examples. Focused on delivering a reproducible validation workflow for subclonal deconvolution results to enable cross-caller comparison across PyClone, Viber, and Mobster, enhancing reliability of subclonal inferences and accelerating validation.
2025-06 Monthly Summary for caravagnalab/ProCESS-examples. Focused on delivering a reproducible validation workflow for subclonal deconvolution results to enable cross-caller comparison across PyClone, Viber, and Mobster, enhancing reliability of subclonal inferences and accelerating validation.
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