|Yap, Immanuel - CORNELL UNIVERSITY|
|Kleinberg, Jon - CORNELL UNIVERSITY|
|Mccouch, Susan - CORNELL UNIVERSITY|
Submitted to: Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 20, 2003
Publication Date: December 1, 2003
Citation: YAP, I.V., SCHNEIDER, D.J., KLEINBERG, J., MATTHEWS, D.E., CARTINHOUR, S.W., MCCOUCH, S.R. A GRAPH-THEORETIC APPROACH TO COMPARING AND INTEGRATING GENETIC, PHYSICAL AND SEQUENCE-BASED MAPS. GENETICS. 2003. V. 165. P. 2235-2247. Interpretive Summary: For many species, multiple genetic and physical maps are often available. Each map may contain unique information, and experimentalists must combine the information in order to plan their research. Map integration is particularly complex when many markers are involved and when maps are in disagreement. Although one solution is to produce a consensus map that focuses on points of agreement, valuable information about disagreements is lost. This paper describes a mathematical approach to map integration that preserves all the information in the original maps and makes it possible to identify both agreements and disagreements easily. The result should help researchers design experiments to resolve map differences and produce more accurate maps.
Technical Abstract: 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 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.