Abstract
We use the subset containment relation to construct a probabilistic nonadaptive group testing design and decoding algorithm that, in the presence of testing errors, identifies many positives in a population. We give a lower bound for the expected portion of positives identified as a function of an upper bound on the number of testing errors.
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The algorithms contained herein are part of The State University of New York Research Foundation invention C1230-125, Probabilistic and Combinatorial Nonadaptive and Two-Stage Group Testing and DNA Library Screening by A. Macula and K. Anne.
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Macula, A.J. Probabilistic nonadaptive group testing in the presence of errors and DNA library screening. Annals of Combinatorics 3, 61–69 (1999). https://doi.org/10.1007/BF01609876
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DOI: https://doi.org/10.1007/BF01609876