Bounds on the minimum mosaic of population sequences under recombination

Authors:
Yufeng Wu
Affiliations:
Department of Computer Science and Engineering, University of Connecticut, Storrs, CT
Venue:
CPM'10 Proceedings of the 21st annual conference on Combinatorial pattern matching
Year:
2010

Citing 8
Cited 2

Methods for Inferring Block-Wise Ancestral History from Haploid Sequences

WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
Finding Founder Sequences from a Set of Recombinants

WABI '02 Proceedings of the Second International Workshop on Algorithms in Bioinformatics
Genotype Sequence Segmentation: Handling Constraints and Noise

WABI '08 Proceedings of the 8th international workshop on Algorithms in Bioinformatics
An analytical upper bound on the minimum number of recombinations in the history of SNP sequences in populations

Information Processing Letters
Tabu Search for the Founder Sequence Reconstruction Problem: A Preliminary Study

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living
A hidden markov technique for haplotype reconstruction

WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Haplotype inference via hierarchical genotype parsing

WABI'07 Proceedings of the 7th international conference on Algorithms in Bioinformatics
Improved algorithms for inferring the minimum mosaic of a set of recombinants

CPM'07 Proceedings of the 18th annual conference on Combinatorial Pattern Matching

Minimum mosaic inference of a set of recombinants

CATS '11 Proceedings of the Seventeenth Computing: The Australasian Theory Symposium - Volume 119
Minimum mosaic inference of a set of recombinants

CATS 2011 Proceedings of the Seventeenth Computing on The Australasian Theory Symposium - Volume 119

Quantified Score

Hi-index	0.00

Visualization

Abstract

We study the minimum mosaic problem, an optimization problem originated in population genomics. We develop a new lower bound, called the C bound. The C bound is provably higher and significantly more accurate in practice than an existing bound. We show how to compute the exact C bound using integer linear programming. We also show that a weaker version of the C bound is also more accurate than the existing bound, and can be computed in polynomial time. Simulation shows that the new bounds often match the exact optimum at least for the range of data we tested. Moreover, we give an analytical upper bound for the minimum mosaic problem.