Accurate Construction of Consensus Genetic Maps via Integer Linear Programming

—We study the problem of merging genetic maps, when the individual genetic maps are given as directed acyclic graphs. The computational problem is to build a consensus map, which is a directed graph that includes and is consistent with all (or, the vast majority of) the markers in the input maps. However, when markers in the individual maps have ordering conflicts, the resulting consensus map will contain cycles. Here, we formulate the problem of resolving cycles in the context of a parsimonious paradigm that takes into account two types of errors that may be present in the input maps, namely local reshuffles and global displacements. The resulting combinatorial optimization problem is in turn expressed as an integer linear program. A fast approximation algorithm is proposed, and an additional speed-up heuristic is developed. Our algorithms were implemented in a software tool named MERGEMAP which is freely available for academic use. An extensive set of experiments show that MERGEM...

• Type: Journal
• Year: 2011
• Where: TCBB
• Authors: Yonghui Wu, Timothy J. Close, Stefano Lonardi
• Keywords: Consensus Map, Genetic Maps, Individual Genetic Maps, Software Engineering, TCBB 2011