scholarly journals Уштеда тестова удруживањем узорака

2020 ◽  
Author(s):  
Dimitrije Čvokić
Keyword(s):  
Pooling Design

Увод/циљ: Сврха алгоритама групног тестирања јесте да обезбједе рационализацију ресурса. Стога, очекује се да се њиховим коришћењем могу, такође, остварити одређене уштеде при масовном тестирању RT(q)PCR методом ради идентификације заражених вирусом САРСКоВ2.Методе: Предочена су два приступа неадаптивног групног тестирања заснованог на удруживању узорака, у англојезичној литератури познатом као pooling design: Хвангов алгоритам уопштеног цијепања и матрична стратегија.Резултати: Уз дискусију добрих и лоших страна наведене су и оцјене максималног броја тестова. Матрична стратегија представљена је својеврсном модификацијом која смањује поменуту оцјену, а, с друге стране, не утиче много на комплексност процедуре, што је значајно за њену примјену у пракси.Закључак: Узимајући у обзир тренутну ситуацију, има смисла разматрати овакву врсту рационализације ресурса, ради повећања ефикасности епидемиолошкихмјера.

scholarly journals Accuracy of GEBV of sires based on pooled allele frequency of their progeny

2021 ◽  
Author(s):  
Napoleón Vargas Jurado ◽  
Larry A Kuehn ◽  
John W Keele ◽  
Ronald M Lewis
Keyword(s):  
Allele Frequency ◽  
Significant Interaction ◽  
Small Ruminants ◽  
Pool Size ◽  
Pedigree Information ◽  
Technical Error ◽  
Pooling Design ◽  
Sheep Population ◽  
Genomic Breeding ◽  
Potential Sources

Abstract Despite decreasing genotyping costs, in some cases individually genotyping animals is not economically feasible (e.g., in small ruminants). An alternative is to pool DNA, using the pooled allele frequency (PAF) to garner information on performance. Still, the use of PAF for prediction (estimation of genomic breeding values; GEBV) has been limited. Two potential sources of error on accuracy of GEBV of sires, obtained from PAF of their progeny themselves lacking pedigree information, were tested: i) pool construction error (unequal contribution of DNA from animals in pools), and ii) technical error (variability when reading the array). Pooling design (random, extremes, K-means), pool size (5, 10, 25, 50 and 100 individuals), and selection scenario (random, phenotypic) also were considered. These factors were tested by simulating a sheep population. Accuracy of GEBV—the correlation between true and estimated values—was not substantially affected by pool construction or technical error, or selection scenario. A significant interaction, however, between pool size and design was found. Still, regardless of design, mean accuracy was higher for pools of 10 or less individuals. Mean accuracy of GEBV was 0.174 (SE 0.001) for random pooling, and 0.704 (SE 0.004) and 0.696 (SE 0.004) for extreme and K-means pooling, respectively. Non-random pooling resulted in moderate accuracy of GEBV. Overall, pooled genotypes can be used in conjunction with individual genotypes of sires for moderately accurate predictions of their genetic merit with little effect of pool construction or technical error.

Asymptotics of pooling design performance

1999 ◽  
Vol 36 (04) ◽  
pp. 951-964
Author(s):  
J. K. Percus ◽  
O. E. Percus ◽  
W. J. Bruno ◽  
D. C. Torney
Keyword(s):  
Group Testing ◽  
Performance Criterion ◽  
Expected Number ◽  
Pooling Design ◽  
Pooling Designs ◽  
Parametric Control ◽  
Expected Performance ◽  
Qualitative Effect ◽  
Pooling Strategy ◽  
Asymptotic Forms

We analyse the expected performance of various group testing, or pooling, designs. The context is that of identifying characterized clones in a large collection of clones. Here we choose as performance criterion the expected number of unresolved ‘negative’ clones, and we aim to minimize this quantity. Technically, long inclusion–exclusion summations are encountered which, aside from being computationally demanding, give little inkling of the qualitative effect of parametric control on the pooling strategy. We show that readily-interpreted re-summation can be performed, leading to asymptotic forms and systematic corrections. We apply our results to randomized designs, illustrating how they might be implemented for approximating combinatorial formulae.

Improved construction for pooling design

2007 ◽  
Vol 15 (1) ◽  
pp. 123-126 ◽  
Author(s):  
Ping Deng ◽  
F. K. Hwang ◽  
Weili Wu ◽  
David MacCallum ◽  
Feng Wang ◽  
...  
Keyword(s):  
Pooling Design

DNA Screening, Pooling Design and Simplicial Complex

2003 ◽  
Vol 7 (4) ◽  
pp. 389-394 ◽  
Author(s):  
Haesun Park ◽  
Weili Wu ◽  
Zhen Liu ◽  
Xiaoyu Wu ◽  
Hong G. Zhao
Keyword(s):  
Simplicial Complex ◽  
Pooling Design

Asymptotics of pooling design performance

1999 ◽  
Vol 36 (4) ◽  
pp. 951-964 ◽  
Author(s):  
J. K. Percus ◽  
O. E. Percus ◽  
W. J. Bruno ◽  
D. C. Torney
Keyword(s):  
Group Testing ◽  
Performance Criterion ◽  
Expected Number ◽  
Pooling Design ◽  
Pooling Designs ◽  
Parametric Control ◽  
Expected Performance ◽  
Qualitative Effect ◽  
Pooling Strategy ◽  
Asymptotic Forms

We analyse the expected performance of various group testing, or pooling, designs. The context is that of identifying characterized clones in a large collection of clones. Here we choose as performance criterion the expected number of unresolved ‘negative’ clones, and we aim to minimize this quantity. Technically, long inclusion–exclusion summations are encountered which, aside from being computationally demanding, give little inkling of the qualitative effect of parametric control on the pooling strategy. We show that readily-interpreted re-summation can be performed, leading to asymptotic forms and systematic corrections. We apply our results to randomized designs, illustrating how they might be implemented for approximating combinatorial formulae.

scholarly journals A NEW CONSTRUCTION FOR POOLING DESIGNS

2011 ◽  
Vol 85 (1) ◽  
pp. 121-127
Author(s):  
FENGLIANG JIN ◽  
HOUCHUN ZHOU ◽  
JUAN XU
Keyword(s):  
Library Screening ◽  
Pooling Design ◽  
Pooling Designs ◽  
Disjunct Matrix ◽  
Helpful Tool ◽  
Dna Library ◽  
New Family ◽  
New Construction ◽  
Dna Library Screening ◽  
Disjunct Matrices

AbstractPooling designs are a very helpful tool for reducing the number of tests for DNA library screening. A disjunct matrix is usually used to represent the pooling design. In this paper, we construct a new family of disjunct matrices and prove that it has a good row to column ratio and error-tolerant property.

scholarly journals DECONVOLUTING BAC–GENE RELATIONSHIPS USING A PHYSICAL MAP

2008 ◽  
Vol 06 (03) ◽  
pp. 603-622
Author(s):  
YONGHUI WU ◽  
LAN LIU ◽  
TIMOTHY J. CLOSE ◽  
STEFANO LONARDI
Keyword(s):  
Physical Map ◽  
Bac Library ◽  
Artificial Chromosome ◽  
Hybridization Experiment ◽  
Pooling Design ◽  
Bac Clones ◽  
Hybridization Data ◽  
A Genome ◽  
The Right ◽  
Combinatorial Pooling

Deconvolution of relationships between bacterial artificial chromosome (BAC) clones and genes is a crucial step in the selective sequencing of regions of interest in a genome. It often includes combinatorial pooling of unique probes obtained from the genes (unigenes), and screening of the BAC library using the pools in a hybridization experiment. Since several probes can hybridize to the same BAC, in order for the deconvolution to be achievable the pooling design has to be able to handle a large number of positives. As a consequence, smaller pools need to be designed, which in turn increases the number of hybridization experiments, possibly making the entire protocol unfeasible. We propose a new algorithm that is capable of producing high-accuracy deconvolution even in the presence of a weak pooling design, i.e. when pools are rather large. The algorithm compensates for the decrease of information in the hybridization data by taking advantage of a physical map of the BAC clones. We show that the right combination of combinatorial pooling and our algorithm not only dramatically reduces the number of pools required, but also successfully deconvolutes the BAC–gene relationships with almost perfect accuracy. Software is available on request from the first author.

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