Too many alternative trees - and how to evaluate them?

[stefmldk]

Dear CONIPHER team

Thanks again for providing this software!

I wonder if it would be possible to limit the number of alternative trees that makes it into the alternative trees plot? I have a dataset that results in 13800 possible trees, which makes the pytree_multipletrees.pdf file very large and impossible to open (506 MB). Perhaps it would be possible to define a default max value or let the user define a suitable value?
Alternatively, to even make it feasible to evaluate alternative trees in such cases where there are many, would it be possible to filter out trees that are very close in edge_probability_score? Perhaps do a clustering of sorts based on edge_probability_score and pick the tree with the highest score from each cluster? Lastly it would be great to have a more relatable p-value associated with each tree - for instance, for each proposed tree, what is the probability of getting the input dataset of observed variant allele frequencies assuming CNVs are inferred correctly - or something.

Cheers,
Steffen

[Elpalet]

I think based on the current version, unless you only have a small number of patients, it is feasible to use the optimal tree.

[stefmldk]

I am not sure I understand @Elpalet. Each tree - both the optimal and alternative trees - refer to one patient only. But you typically have several samples for each patient representing either primary tumor or metastases.

[Elpalet]

I am not sure I understand @Elpalet. Each tree - both the optimal and alternative trees - refer to one patient only. But you typically have several samples for each patient representing either primary tumor or metastases.

I don't know how many samples one of your patients has? Is it enough? I used CONIPHER for each patient individually, rather than running them all together.