Offer conversions from one to another genetic map

[gregorgorjanc]

Convert mapping functions - providing a genetic map and implementing it with the gamma-sprinkling model

• This paper describes a software that infers parameters of the gamma-sprinkling model: CODA (crossover distribution analyzer): quantitative characterization of crossover position patterns along chromosomes https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-27

• Genetic Map Functions https://onlinelibrary.wiley.com/doi/full/10.1002/0470011815.b2a05037 by Speed

The Speed paper (or his older work) talks about a generic mapping functions used for the gamma model (gamma-sprinkling model uses two parameters for interference and we should be able to convert any value for these parameters to map choice)

[gaynorr]

I've thought about this some more and I think it is best to not offer genetic map conversions. This functionality would help with relatively sparse genetic maps, but isn't needed for dense maps. Genetic map distance can be estimated fairly accurately regardless of the mapping function when markers are very close. This is because it is highly unlikely for there to be more than one crossover between these markers.

In most cases, we can probably assume that the map is correct and what is really of interest to the user is modeling crossover interference correctly to match observed recombination rates. This would be best accomplished using a tool like CODA and putting the parameters the tool estimates into AlphaSimR. Alternative, the user can try a few common presents (e.g. Kosambi vs Haldane like interference models) to quantify the impact of crossover interference.