Comparison of Costs for Multi-Stage Group Testing Methods in the Pharmaceutical Industry

Comparison of Group Testing Algorithms for Case Identification in the Presence of Test Error

“…Pooling of specimens to increase efficiency of screening individuals for rare diseases has a long history, dating back to screening for syphilis in military inductees in the 1940s (Dorfman, 1943). Subsequently, specimen pooling or group testing has been applied to screening for many other infectious diseases (Kacena et al, 1998; Quinn et al, 2000; Centers for Disease Control and Prevention, 2003) and has also found broader application in entomology (Venette, Moon, and Hutchinson, 2002), screening for genetic mutations (Gastwirth, 2000), the blood bank and pharmaceutical industries (Jones and Zhigljavsky, 2001), and many other areas. In the context of infectious diseases, group testing is typically used for (i) case identification, i.e., detecting all individuals having the disease of interest and (ii) prevalence estimation, i.e., estimating the proportion of individuals in the population having a particular disease.…”

Identifying Rare Variants With Optimal Depth of Coverage and Cost‐Effective Overlapping Pool Sequencing

“…The concept of GT can date back to World War II, which was first proposed by Dorfman [Dorfman, 1943], for the problem of determining which blood samples contain the syphilis antigen (defective also called positive samples) for numerous soldiers. For now, many biological applications benefit from the GT such as blood testing [Ding-Zhu and Hwang, 2000;Dorfman, 1943;Sobel and Groll, 1959], HIV testing [Hughes-Oliver, 2006;Kim et al, 2007;Westreich et al, 2008], clone library screening [Balding and Torney, 1997;Bruno et al, 1995;Knill et al, 1996], protein-protein interaction mapping [Jin et al, 2007;Jin et al, 2006;Vermeirssen et al, 2007;Xin et al, 2009], drug screening [Jones and Zhigljavsky, 2001;Kainkaryam and Woolf, 2008;Kainkaryam and Woolf, 2009;Wilson-Lingardo et al, 1996] and population genotyping [Erlich et al, 2009a;Erlich et al, 2009b;Patterson and Gabriel, 2009;Prabhu and Pe'Er, 2009]. Combine with GT, fewer DNA libraries are required to detect rare variants.…”

Rejoinder to “Reader Reaction: A Note on the Evaluation of Group Testing Algorithms in the Presence of Misclassification”

“…The earlier articles by McMahan et al () and Kim et al () also acknowledge the need for (i). Regarding (ii), the group testing literature has a long history of objective (or cost) functions being proposed in order to optimize design of group testing experiments (e.g., see Graff and Roeloffs, ; Burns and Mauro, ; Langfeldt et al, ; Jones and Zhigljavsky, ; Kennedy, ; Bar‐Lev et al, ; and Liu et al, among others). Like MAR, previously proposed cost functions typically combine the expected number of tests, a penalty for misclassification, and/or the actual monetary cost associated with various aspects of the procedure.…”