Elsevier

Discrete Applied Mathematics

Volume 155, Issue 3, 1 February 2007, Pages 288-299
Discrete Applied Mathematics

Overlaps help: Improved bounds for group testing with interval queries

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Abstract

Given a finite ordered set of items and an unknown distinguished subset P of up to p positive elements, identify the items in P by asking the least number of queries of the type ‘‘does the subset Q intersect P?”, where Q is a subset of consecutive elements of {1,2,,n}. This problem arises, e.g., in computational biology, in a particular method for determining splice sites in genes. We consider time-efficient algorithms where queries are arranged in a fixed number s of stages: In each stage, queries are performed in parallel. In a recent bioinformatics paper, we proved optimality (subject to lower-order terms) with respect to the number of queries, of some strategies for the special cases p=1 or s=2. Exploiting new ideas, we are now able to provide improved lower bounds for any p2 and s3 and improved upper bounds for larger s. Most notably, our new bounds converge as s grows. Our new query scheme uses overlapping query intervals within a stage, which is effective for large enough s. This contrasts with our previous results for s2 where optimal strategies were implemented by disjoint queries. The main open problem is whether overlaps help already in the case of small s3. Anyway, the remaining gaps between the current upper and lower bounds for any fixed s3 amount to small constant factors in the main term. The paper ends with a discussion of practical implications in the case that the positive elements are well separated.

Keywords

Group testing
Interval query
Non-adaptive strategy
Computational molecular biology

Cited by (0)

Part of the results appeared in preliminary form in the Proceedings of the 11th International Computing and Combinatorics Conference COCOON 2005, Lecture Notes in Computer Science (Springer), vol. 3595, pp. 935-944.

1

Supported by DAAD-Grant no. A/04/33535 and by the Sofja Kovalevskaja Award 2004 of the Alexander von Humboldt Foundation.

2

Partially supported by the Swedish Research Council (Vetenskapsrådet), project “Algorithms for searching and inference in genetics”, Grant no. 621-2002-4574.