title: RHO--radiation hybrid ordering.
abstract: Radiation hybrid (RH) mapping is a somatic cell technique that is used for ordering markers along a chromosome and estimating the physical distances between them. With the advent of this mapping technique, analyzing the experimental data is becoming a challenging and demanding computational task. In this paper we present the software package RHO (radiation hybrid ordering). The package implements a number of heuristics that attempt to order genomic markers along a chromosome, given as input the results of an RH experiment. The heuristics are based on reducing an appropriate optimization problem to the traveling salesman problem (TSP). The reduced optimization problem is either the nonparametric obligate chromosome breaks (OCBs) or the parametric maximum likelihood estimation (MLE). We tested our package on both simulated and publicly available RH data. For synthetic RH data, the reconstructed markers' permutation is very close to the original permutation, even with fairly high error rates. For real data we used the framework markers' data from the Whitehead Institute maps. For most of the chromosomes (18 out of 23), there is a perfect agreement or nearly perfect agreement (reversal of chromosome arm or arms) between our maps and the Whitehead framework maps. For the remaining five chromosomes, our maps improve on the Whitehead framework maps with respect to both optimization criteria, having higher likelihood and fewer breakpoints. For three chromosomes, the results differ significantly (lod score >1.75), with chromosome 2 having the largest improvement (lod score 3.776).
authors.affiliation: Department of Computer Science, Technion, Haifa 32000, Israel. amirbd@cs.washington.edu
authors.forename: A
authors.initials: A
authors.lastname: Ben-Dor
authors.forename: B
authors.initials: B
authors.lastname: Chor
authors.forename: D
authors.initials: D
authors.lastname: Pelleg
mesh_terms: D000465:Algorithms; D019457:Chromosome Breakage; D002874:Chromosome Mapping / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D005819:Genetic Markers; D006801:Humans; D006822:Hybrid Cells; D016013:Likelihood Functions; D012984:Software
chemical_list: D005819:Genetic Markers