As I understand, sciClone uses estimates of variant allele frequency (VAF) in copy-neutral regions to estimate subclonality (thus, in a manner, not using CNV info. Please correct me if I am wrong).
The exome sequencing data, I have got, has relatively fewer mutations and a higher variation in copy number. When I remove the non-neutral copy number regions (copy number != 2), I am left with very few mutations. Given that I have multiple samples for each case, the resulting VAF matrix becomes very sparse leading to poor results.
I was wondering if I can complement the VAF with copy number and ploidy to compute cancer cell fraction (http://www.nature.com/leu/journal/v28/n1/fig_tab/leu2013248f1.html#figure-title) or, alternatively, compute cell prevalence (CP) values using PyClone or ASCAT, and feed that into sciClone. Will sciClone clustering work as it does when using VAFs? If yes, that's excellent; if not, can you recommend some alternative tool for subclonal reconstruction.