Published April 9, 2023 | Version 2
Software Open

An R function implementing the "All Marker Alleles" (AMA) algorithm

  • 1. Cinvestav

Description

The "AMA" R function implements the "All Marker Alleles" algorithm as described in (Hayano-Kanashiro et al. 2017). 
For details of the algorithm please see the supplementary file "ece32754-sup-0001-DataS1.pdf" of that paper that you can download from the URL:

https://onlinelibrary.wiley.com/doi/10.1002/ece3.2754

Download directly from ece32754-sup-0001-DataS1.pdf

In summary, given a matrix of accessions (rows) and frequencies of different genetic markers (columns), the algorithm selects the minimum collection of accessions that contains all genetic markers.

In many cases this algorithm dramatically reduces the collection of accessions to a "core" collection which represents all genetic diversity present in the larger original collection. This is useful to prioritize germplasm for conservation proposes.

Additionally, the function produces a rareness coefficient for each one of the accessions. This could be also useful to prioritize conservation of germplasm.

The algorithm is exemplified with a collection of 1338 Mexican maize accessions which are genotyped for a total of 333 combination of SSR marker/allele combinations; see 

Martínez O., Ceniceros-Ojeda A., Hayano-Kanashiro C., Reyes-Valdés H., Pons-Hernández J.L. and Simpson J. "Criteria for prioritizing selection of Mexican maize landrace accessions for conservation in situ or ex situ based on phylogenetic analysis". 2023 (In preparation).

Notes

This research was supported by FO-CIBIOGEM-143919 (Mexican government).

Files

AMA2023.RData.zip

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Additional details

Related works

Is supplement to
Journal article: 10.1002/ece3.2754 (DOI)

References

  • Hayano-Kanashiro C, Martínez de la Vega O, Reyes-Valdés MH, et al. An SSR-based approach incorporating a novel algorithm for identification of rare maize genotypes facilitates criteria for landrace conservation in Mexico. Ecol Evol. 2017;7:1680–1690. https://doi.org/ 10.1002/ece3.2754