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Integration of genetic maps by polynomial transformations
Currently available genetic maps differ in a variety of basic features; in particular, with respect to the total length of the genome. Consequently, the question arises as to the extent to which genetic maps are compatible to each other, as well as to the methods with which genetic maps can be trans...
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Published in: | American journal of medical genetics 2000-02, Vol.96 (1), p.108-113 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Currently available genetic maps differ in a variety of basic features; in particular, with respect to the total length of the genome. Consequently, the question arises as to the extent to which genetic maps are compatible to each other, as well as to the methods with which genetic maps can be transformed into one another. We propose a set of nonlinear, polynomial transformations that enable the integration of genetic maps at a sufficiently high overall precision. Our analysis of six major, publicly available maps, and iteratively optimized polynomials of up to degree 5, yielded differences of ≤ ±0.8 cM between empirical and reconstructed marker locations for >90% of points. Similarly, we determined, at a slightly worse overall fit, those polynomials that enabled the reconstruction of sex‐specific recombination estimates from sex‐averaged data. Our results suggest that polynominal transformations may become a valuable extension of standard map construction methods due to a rapid integration of newly developed markers into existing maps. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:108–113, 2000. © 2000 Wiley‐Liss, Inc. |
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ISSN: | 0148-7299 1096-8628 |
DOI: | 10.1002/(SICI)1096-8628(20000207)96:1<108::AID-AJMG21>3.0.CO;2-J |