Dear developers of PyClone-VI,
Thank you for developing such a valuable tool.
I have a question regarding the use of additional cluster filtering based on COSMIC mutational signatures, as done in Lahtinen et al. (2023), "Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high-grade serous carcinoma". In that study, clusters with a high proportion of likely artefactual mutations were excluded by comparing them to known mutational signatures from the cosmic database.
Would this approach be particularly advisable when working with datasets with limited coverage, such as WGS at ~36× depth, as used in their study? Or are there other scenarios where incorporating such signature-based filtering into the PyClone-VI workflow would also be beneficial?
Best regards, Sanne Hoefnagel, Endeavor consortium
Dear developers of PyClone-VI,
Thank you for developing such a valuable tool.
I have a question regarding the use of additional cluster filtering based on COSMIC mutational signatures, as done in Lahtinen et al. (2023), "Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high-grade serous carcinoma". In that study, clusters with a high proportion of likely artefactual mutations were excluded by comparing them to known mutational signatures from the cosmic database.
Would this approach be particularly advisable when working with datasets with limited coverage, such as WGS at ~36× depth, as used in their study? Or are there other scenarios where incorporating such signature-based filtering into the PyClone-VI workflow would also be beneficial?
Best regards, Sanne Hoefnagel, Endeavor consortium