The Detection of Defective Members of Large Populations
01 Dec 1943-Annals of Mathematical Statistics (Institute of Mathematical Statistics)-Vol. 14, Iss: 4, pp 436-440
About: This article is published in Annals of Mathematical Statistics.The article was published on 1943-12-01 and is currently open access. It has received 1533 citations till now.
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TL;DR: Recent developments in quantitative genotyping assays and in the design and analysis of pooling studies are discussed.
Abstract: DNA pooling is a practical way to reduce the cost of large-scale association studies to identify susceptibility loci for common diseases. Pooling allows allele frequencies in groups of individuals to be measured using far fewer PCR reactions and genotyping assays than are used when genotyping individuals. Here, we discuss recent developments in quantitative genotyping assays and in the design and analysis of pooling studies. Sophisticated pooling designs are being developed that can take account of hidden population stratification, confounders and inter-loci interactions, and that allow the analysis of haplotypes.
582 citations
578 citations
TL;DR: In this article, the problem of finding the best integer x for the first test and to find a rule for choosing the best subsequent test-groups (which may depend on results already observed), in order to minimize the expected total number of group-tests required to classify each of the N units as good or defective is considered.
Abstract: In group-testing, a set of x units is taken from a total starting set of N units, and the x units (1 ≤ × ≤ N) are tested simultaneously as a group with one of two possible outcomes: either all x units are good or at least one defective unit is present (we don't know how many or which ones). Under this type of testing, the problem is to find the best integer x for the first test and to find a rule for choosing the best subsequent test-groups (which may depend on results already observed), in order to minimize the expected total number of group-tests required to classify each of the N units as good or defective. It is assumed that the N units can be treated like independent binomial chance variables with a common, known probability p of any one being defective; the case of unknown p and several generalizations of the problem are also considered.
359 citations
TL;DR: It is hoped that implementation of a pool test for COVID-19 would allow expanding current screening capacities thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.
Abstract: BACKGROUND: The recent emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to a current pandemic of unprecedented scale. Although diagnostic tests are fundamental to the ability to detect and respond, overwhelmed healthcare systems are already experiencing shortages of reagents associated with this test, calling for a lean immediately applicable protocol. METHODS: RNA extracts of positive samples were tested for the presence of SARS-CoV-2 using reverse transcription quantitative polymerase chain reaction, alone or in pools of different sizes (2-, 4-, 8-, 16-, 32-, and 64-sample pools) with negative samples. Transport media of additional 3 positive samples were also tested when mixed with transport media of negative samples in pools of 8. RESULTS: A single positive sample can be detected in pools of up to 32 samples, using the standard kits and protocols, with an estimated false negative rate of 10%. Detection of positive samples diluted in even up to 64 samples may also be attainable, although this may require additional amplification cycles. Single positive samples can be detected when pooling either after or prior to RNA extraction. CONCLUSIONS: As it uses the standard protocols, reagents, and equipment, this pooling method can be applied immediately in current clinical testing laboratories. We hope that such implementation of a pool test for coronavirus disease 2019 would allow expanding current screening capacities, thereby enabling the expansion of detection in the community, as well as in close organic groups, such as hospital departments, army units, or factory shifts.
354 citations