A note on statistical repeatability and study design for high-throughput assays

Nicholson, George; Holmes, Chris

doi:10.1002/sim.7175

Cited by 10 publications

(6 citation statements)

References 30 publications

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“…The SD of the fall is assumed to be 12.5 mmHg and the cost of enrolling a subject is estimated to be 15 times the cost of making an additional measurement on an enrolled subject. The ICC for repeat systolic measurements is assumed to be 0.67 [ 3 ]. The use of multiple measures at baseline and 12 m is being considered.…”

Section: Resultsmentioning

confidence: 99%

“…A sample size calculation based on the above Glynn and Rosner example suggests that a standardized difference of 0.4 in a binary predictive factor could be detected with 80% power using 197 single eyes; this decreases to a standardized difference of 0.25 if both eyes ( N = 394) are studied. Nicholson and Holmes [ 3 ] noted that a popular but improper method for assessing high-throughput assays’ precision is by scatter-plotting data. This consists of equally dividing a sample and assaying the two halves separately, then plotting and correlating all analytes’ results in the first half versus the second half.…”

Section: Introductionmentioning

confidence: 99%

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Employing multiple synchronous outcome samples per subject to improve study efficiency

A’Hern¹

2021

BMC Med Res Methodol

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Background Accuracy can be improved by taking multiple synchronous samples from each subject in a study to estimate the endpoint of interest if sample values are not highly correlated. If feasible, it is useful to assess the value of this cluster approach when planning studies. Multiple assessments may be the only method to increase power to an acceptable level if the number of subjects is limited. Methods The main aim is to estimate the difference in outcome between groups of subjects by taking one or more synchronous primary outcome samples or measurements. A summary statistic from multiple samples per subject will typically have a lower sampling error. The number of subjects can be balanced against the number of synchronous samples to minimize the sampling error, subject to design constraints. This approach can include estimating the optimum number of samples given the cost per subject and the cost per sample. Results The accuracy improvement achieved by taking multiple samples depends on the intra-class correlation (ICC). The lower the ICC, the greater the benefit that can accrue. If the ICC is high, then a second sample will provide little additional information about the subject’s true value. If the ICC is very low, adding a sample can be equivalent to adding an extra subject. Benefits of multiple samples include the ability to reduce the number of subjects in a study and increase both the power and the available alpha. If, for example, the ICC is 35%, adding a second measurement can be equivalent to adding 48% more subjects to a single measurement study. Conclusion A study’s design can sometimes be improved by taking multiple synchronous samples. It is useful to evaluate this strategy as an extension of a single sample design. An Excel workbook is provided to allow researchers to explore the most appropriate number of samples to take in a given setting.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Employing multiple synchronous outcome samples per subject to improve study efficiency

A’Hern¹

2021

BMC Med Res Methodol

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show abstract

“…Related fields of functional genomics, such as transcriptomics, have seen considerable interest in controlling for different experimental sources of variation, broadly labeled as batch effects [28,[62][63][64][65][66][67]. These studies have shown that differences between batches first need to be corrected to avoid erroneous conclusions [68].…”

Section: Discussionmentioning

confidence: 99%

A Bayesian non-parametric mixed-effects model of microbial growth curves

et al. 2020

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Substantive changes in gene expression, metabolism, and the proteome are manifested in overall changes in microbial population growth. Quantifying how microbes grow is therefore fundamental to areas such as genetics, bioengineering, and food safety. Traditional parametric growth curve models capture the population growth behavior through a set of summarizing parameters. However, estimation of these parameters from data is confounded by random effects such as experimental variability, batch effects or differences in experimental material. A systematic statistical method to identify and correct for such confounding effects in population growth data is not currently available. Further, our previous work has demonstrated that parametric models are insufficient to explain and predict microbial response under non-standard growth conditions. Here we develop a hierarchical Bayesian non-parametric model of population growth that identifies the latent growth behavior and response to perturbation, while simultaneously correcting for random effects in the data. This model enables more accurate estimates of the biological effect of interest, while better accounting for the uncertainty due to technical variation. Additionally, modeling hierarchical variation provides estimates of the relative impact of various confounding effects on measured population growth.

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“…To improve the detectable δ 13 C and δ 15 N separation between captive and wild groups or to increase effect size differences, the variance of each hierarchal level of sampling (indi-vidual > scute > sample) needed to be minimised without oversampling (Nicholson and Holmes 2017). A pilot analysis was performed to provide estimates of the variances of each hierarchal level of sampling.…”

Section: Sampling Size and Designmentioning

confidence: 99%

Pet or pest? Stable isotope methods for determining the provenance of an invasive alien species

Hill¹,

Nielson²,

Tyler³

et al. 2020

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The illegal pet trade facilitates the global dispersal of invasive alien species (IAS), providing opportunities for new pests to establish in novel recipient environments. Despite the increasing threat of IAS to the environment and economy, biosecurity efforts often lack suitable, scientifically-based methods to make effective management decisions, such as identifying an established IAS population from a single incursion event. We present a proof-of-concept for a new application of a stable isotope technique to identify wild and captive histories of an invasive pet species. Twelve red-eared slider turtles (Trachemys scripta elegans) from historic Australian incursions with putative wild, captive and unknown origins were analysed to: (1) present best-practice methods for stable isotope sampling of T. s. elegans incursions; (2) effectively discriminate between wild and captive groups using stable isotope ratios; and (3) present a framework to expand the methodology for use on other IAS species. A sampling method was developed to obtain carbon (δ13C) and nitrogen (δ15N) stable isotope ratios from the keratin layer of the carapace (shells), which are predominantly influenced by dietary material and trophic level respectively. Both δ13C and δ15N exhibited the potential to distinguish between the wild and captive origins of the samples. Power simulations demonstrated that isotope ratios were consistent across the carapace and a minimum of eight individuals were required to effectively discriminate wild and captive groups, reducing overall sampling costs. Statistical classification effectively separated captive and wild groups by δ15N (captive: δ15N‰ ≥ 9.7‰, minimum of 96% accuracy). This study outlines a practical and accessible method for detecting IAS incursions, to potentially provide biosecurity staff and decision-makers with the tools to quickly identify and manage future IAS incursions.

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A note on statistical repeatability and study design for high-throughput assays

Cited by 10 publications

References 30 publications

Employing multiple synchronous outcome samples per subject to improve study efficiency

Employing multiple synchronous outcome samples per subject to improve study efficiency

A Bayesian non-parametric mixed-effects model of microbial growth curves

Pet or pest? Stable isotope methods for determining the provenance of an invasive alien species

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