Optimal two-stage algorithms for group testing problems

Annalisa De Bonis, Leszek Ga̧sieniec, Ugo Vaccaro

Research output: Contribution to journalArticle

88 Scopus citations

Abstract

Group testing refers to the situation in which one is given a set of objects script O sign, an unknown subset P ⊆ script O sign, and the task of determining P by asking queries of the type "does P intersect Q?", where Q is a subset of script O sign. Group testing is a basic search paradigm that occurs in a variety of situations such as quality control testing, searching in storage systems, multiple access communications, and data compression, among others. Group testing procedures have been recently applied in computational molecular biology, where they are used for screening libraries of clones with hybridization probes and sequencing by hybridization. Motivated by particular features of group testing algorithms used in biological screening, we study the efficiency of two-stage group testing procedures. Our main result is the first optimal two-stage algorithm that uses a number of tests of the same order as the information-theoretic lower bound on the problem. We also provide efficient algorithms for the case in which there is a Bernoulli probability distribution on the possible sets P, and an optimal algorithm for the case in which the outcome of tests may be unreliable because of the presence of "inhibitory" items in script O sign. Our results depend on a combinatorial structure introduced in this paper. We believe that it will prove useful in other contexts, too.

Original languageEnglish (US)
Pages (from-to)1253-1270
Number of pages18
JournalSIAM Journal on Computing
Volume34
Issue number5
DOIs
StatePublished - Oct 31 2005
Externally publishedYes

Keywords

  • Cover-free families
  • Group testing

ASJC Scopus subject areas

  • Computer Science(all)
  • Mathematics(all)

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