The potential of probabilistic graphical models in linkage map construction.
Volume
130
Pagination
433 - 444
DOI
10.1007/s00122-016-2824-x
Journal
Theor Appl Genet
Issue
Metadata
Show full item recordAbstract
KEY MESSAGE: Probabilistic graphical models show great potential for robust and reliable construction of linkage maps. We show how to use probabilistic graphical models to construct high-quality linkage maps in the face of data perturbations caused by genotyping errors and reciprocal translocations. It has been shown that linkage map construction can be hampered by the presence of genotyping errors and chromosomal rearrangements such as inversions and translocations. Here, we report a novel method for linkage map construction using probabilistic graphical models. The method is proven, both theoretically and practically, to be effective in filtering out markers that contain genotyping errors. In particular, it carries out marker filtering and ordering simultaneously, and is therefore superior to the standard post hoc filtering using nearest-neighbour stress. Furthermore, we demonstrate empirically that the proposed method offers a promising solution to linkage map construction in the case of a reciprocal translocation.