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## Limitations of LAMARC

This documentation has a lot to say about what LAMARC can do. Here is a concise guide to what it cannot do, with some suggestions for other approaches.

### Some combinations of analyses are not possible.

Due to program or mathematical limitations, some combinations of analyses are not possible and will be rejected if attempted:

- Gamma-distributed variation in mutation rate among regions is not compatible with estimation of growth, nor can it currently be used in a Baysian run.
- Newick trees cannot be written out if migration or recombination are allowed.
- Migration rate estimation requires at least two populations.
- Recombination estimation requires at least two linked markers.
- Mapping requires recombination.
- Divergence can only be inferred in a Bayesian run, not a likelihood run.

### Some cases cannot be well modelled by LAMARC.

LAMARC has a wide range of evolutionary models but not all possible ones by any means. Some significant omissions:
- Samples from multiple time points in a fast-evolving population. Consider the BEAST program of Drummond and Rambaut for this.
- Multiple population divergence cases where the population tree is not known. Consider the *BEAST program of Drummond and Rambaut when it is available.
- RFLP, AFLP, or insertion/deletion data. You may be able to use the ARLEQUIN program of Excoffier; we know of no full coalescent likelihood or Bayesian analysis which can handle these data.
- Growth models other than simple exponential growth or decline. Consider the BEAST program of Drummond and Rambaut.
- Geographic isolation as a function of distance, rather than via separation into distinct subpopulations. Consider the Dancing Trees algorithm of Baird, if an implementation becomes available.
- Combining data which have recombination and data which do not (i.e. nuclear and mitochondrial DNA) in the same recombination-aware analysis. We know of no alternative. You may want to do two separate analyses with LAMARC.
- Sequences from multi-gene families. The underlying coalescent model in LAMARC is not correct for such data. Consider the gene-families ML algorithm of Dubb, if an implementation becomes available.
- Recombination rates which vary among regions or across the sequence. Consider the LDHAT program of McVean.

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