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This is a very general outline for the oncoplots. We should prob think about how to handle datasets that contain clinical features and those that don't. They can be easily included and make for powerful visualizations.
Additional CNV calls could be included depending on the analysis run. I don't have a good idea on how to navigate maftools within this setting to allow customisation but keeping them somewhat similar. I imagine providing a gene list, clinical features and a different amount of "top"genes could be useful often, but also things like affected pathways etc. . Anyway to start somewhere:
Prereq: Have a conda environment with maftools installed in it.
This is a very general outline for the oncoplots. We should prob think about how to handle datasets that contain clinical features and those that don't. They can be easily included and make for powerful visualizations.
Additional CNV calls could be included depending on the analysis run. I don't have a good idea on how to navigate maftools within this setting to allow customisation but keeping them somewhat similar. I imagine providing a gene list, clinical features and a different amount of "top"genes could be useful often, but also things like affected pathways etc. . Anyway to start somewhere:
Prereq: Have a conda environment with maftools installed in it.
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