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## Regions and segments

If anyone can suggest better terms here than "regions" and "segments" we will mail them a fine chocolate bar or other confection of their choice. These are unsatisfactory terms but we have failed to find better ones.

LAMARC can handle either pieces of genetic data which are unlinked, or pieces which are pretty tightly linked but perhaps have some recombination. It does not deal well with intermediate cases, several centimorgans apart but still linked. Generally these are better treated as unlinked than as linked, but neither approach is perfect. If you are able to choose the location of your samples, choose either definitely linked or definitely unlinked ones.

We call unlinked areas "regions". Each region represents an independent path through evolutionary history, and will be treated as such. Adding more regions is the best way to improve accuracy of your estimates, except for the estimate of recombination (a single long region is best for recombination).

If your organism does not have sexual reassortment of its genome, it has only one region no matter how many chromosomes it may have. All parts of the genome are inherited as a block. An example would be tracing the history of somatically dividing cells within an organism.

Some regions need to be treated as containing multiple "contiguous segments" of data, often because they need to be modelled differently; for example, a region could contain a stretch of DNA and two microsatellites. These must be treated differently as their mutational process and rates are very different; but if they are adjacent and linked, they are still in the same region. We call subunits within a region "contiguous segments". They may be genetic loci, or simply arbitrary bits of sequence. They do not need to be strictly contiguous (there may be gaps between them) but they should be close enough together to be fairly tightly linked.

For segments to be included in the same region, they should have been sampled from the same haplotypes. If a few haplotypes have missing data for one or more segments, you can supply the missing data as ambiguity symbols ('N' for nucleotide data, '?' for allelic data. The program will reject attempts to put segments into the same region if the names of the individuals or haplotypes do not correspond.

You should model a collection of sequences as a single region if they cover an area no more than a centimorgan or so in length, and you know their relative locations. Each group of sequences which fits this definition should be its own region.

If you are going to estimate recombination, you must know how far apart the segments within each region are, and what order they appear in. If there is no recombination, this information is not necessary (though providing it will do no harm). Distances should be expressed in base pairs. Pinpoint accuracy is probably not necessary, and you do not have to worry about the fact that microsatellites with different repeat numbers are different lengths. It's mainly important to get the scale of the map approximately correct. Clearly you will come to different conclusions about the per-site recombination rate if you think your two segments are separated by a gap of 100 bp or a gap of 10,000 bp.

Within a region, you should model as separate segments any sections which are definitely evolving in different ways. This includes not only DNA versus SNP versus microsatellite data, but possibly also genic versus intergenic stretches of DNA. Also, if a stretch of DNA is interrupted by a microsatellite, it is best to cut the stretch of DNA into a segment before and a segment after the microsatellite, rather than trying to embed one segment in another. (Frankly, we are not sure the program can handle embedded segments.) Breaking a sequence into additional segments slows the program a tiny bit, but has no other bad consequences as far as we know, so when in doubt, subdivide. One pitfall to watch for, however, is that if your nucleotide segments become very short it is unwise to attempt to estimate base frequencies from the data--you may not have a large enough sample, and should substitute an overall estimate of your organism's base frequencies.

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