Clonealign 2.0 contains several updated changes, both to the core model and inference, as well as to
package functionality.
Major changes:
While the modelled expectation remains identical, the likelihood employed is now multinomial
rather than negative binomial. This speeds up inference and removes the need for size factor
and variance calculation.
The preferred package entrypoint is the run_clonealign function, that will run clonealign across
a range of initial parameter values and return the fit that maximizes the ELBO.
New functionality
Post-hoc calculated correlations between the copy number and gene expression are calculated and
assigned to the $correlations slot
Changes to the core model
Multinomial likelihood rather than negative binomial
mu[1] no longer constrained to be 1 to improve optimization in some cases
It is no longer necessary to specify size factors as the multinomial distribution
implicitly conditions on the total counts per cell
Changes to inference
Convergence is monitored by looking at the average change in the previous 10
iterations rather than the single previous iteration, which can be sensitive to random
fluctuations