A graph-theoretic approach to comparing and integrating genetic, physical and sequence-based maps.
For many species, multiple maps are available, often constructed independently by different research groups using different sets of markers and different source material. Integration of these maps provides a higher density of markers and greater genome coverage than is possible using a single study. In this article, we describe a novel approach to comparing and integrating maps by using abstract graphs. A map is modeled as a directed graph in which nodes represent mapped markers and edges define the order of adjacent markers. Independently constructed graphs representing corresponding maps from different studies are merged on the basis of their common loci. Absence of a path between two nodes indicates that their order is undetermined. A cycle indicates inconsistency among the mapping studies with regard to the order of the loci involved. The integrated graph thus produced represents a complete picture of all of the mapping studies that comprise it, including all of the ambiguities and inconsistencies among them. The objective of this representation is to guide additional research aimed at interpreting these ambiguities and inconsistencies in locus order rather than presenting a "consensus order" that ignores these problems.
Yap
Immanuel V
IV
Department of Plant Breeding, Cornell University, Ithaca, New York 14853, USA.
Schneider
David
D
Kleinberg
Jon
J
Matthews
David
D
Cartinhour
Samuel
S
McCouch
Susan R
SR
D002874:Chromosome Mapping; D002875:Chromosomes / Q000235:genetics*; D030561:Databases, Nucleic Acid; D023061:Gene Order / Q000235:genetics*; D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics; D016678:Genome; D008962:Models, Theoretical; D012275:Oryza / Q000235:genetics*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
D005819:Genetic Markers