The symmetric island model with D demes and equal migration rates is often chosen for the investigation of the consequences of population subdivision. Here we show that a stepping-stone model has a more pronounced effect on the genealogy of a sample. For samples from a small geographical region commonly used in genetic studies of humans and Drosophila, there is a shift of the frequency spectrum that decreases the number of low-frequency-derived alleles and skews the distribution of statistics of Tajima, Fu and Li, and Fay and Wu. Stepping-stone spatial structure also changes the two-locus sampling distribution and increases both linkage disequilibrium and the probability that two sites are perfectly correlated. This may cause a false prediction of cold spots of recombination and may confuse haplotype tests that compute probabilities on the basis of a homogeneously mixing population. HOMOGENEOUSLY mixing populations of constant size are a convenient setting to develop the theory of population genetics. However, when one wants to understand patterns observed in data, one must consider the effects of population growth, bottlenecks, and population subdivision. When the consequences of population subdivision are investigated, the symmetric island model with D demes and equal migration rates is the usual choice, and the case of two demes is especially popular. The island model is easy to analyze mathematically due to the fact that if two lineages are not in the same deme, then their relative location is not important. However, this has the unrealistic consequence that after one migration event, the lineage is distributed uniformly over the species range.An alternative approach to modeling spatial structure that does not suffer from this defect is the steppingstone model. In this article, we investigate the consequences of modeling space as a two-dimensional stepping-stone model in which there is an L 3 L grid of colonies and migration only to neighboring colonies. The migration scheme is very simple; however, it results in what Wright called isolation by distance. In other words, it takes a number of migration events for the lineages to spread across the system. As we will see, this feature, which is certainly present in Drosophila and early human populations, causes a dramatic change in the coalescence structure of lineages.The reason for this is intuitively clear. At small times the lineages have not had a chance to spread across the population, so the effective population size is reduced. The coalescence rate is increased, reducing the number of lowfrequency-derived alleles, skewing the site frequency spectrum, and increasing linkage disequilibrium. These effects occur in the island model as well; two lineages sampled from one deme have an increased coalescence rate until one of them migrates, at which point they behave like a random sample from the overall population. In contrast, as we later explain, in the stepping-stone model the effective population size increases roughly linearly in time.The main poin...

Biomarkers assessing cardiovascular function can encompass a wide range of biochemical or physiological measurements. Medical tests that measure biomarkers are typically evaluated for measurement validation and clinical performance in the context of their intended use. General statistical principles for the evaluation of medical tests are discussed in this paper in the context of heart failure. Statistical aspects of study design and analysis to be considered while assessing the quality of measurements and the clinical performance of tests are highlighted. A discussion of statistical considerations for specific clinical uses is also provided. The remarks in this paper mainly focus on methods and considerations for statistical evaluation of medical tests from the perspective of bias and precision. With such an evaluation of performance, healthcare professionals could have information that leads to a better understanding on the strengths and limitations of tests related to heart failure.

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Background In-person pathologist trainings during the COVID-19 pandemic became impossible, necessitating a shift to remote-digital whole slide image (WSI) training. High concordance between WSI and glass slide scores from the same specimens stained with PD-L1 IHC 22C3 pharmDx (SK006) across multiple tumor indications supported the validity of digital training. 1 However, in-person microscope (glass-slide) training versus remote-digital (WSI) training effectiveness must be assessed. Collated testing data on specimens (SK006 stained) spanning multiple indications scored by external pathologists during Agilent led training and testing (T&T) sessions via glass slides were compared to sessions utilizing WSIs. Methods Stained slides (30 unique specimens per tumor indication) were scanned on an Aperio AT2 scanner to generate WSIs for digital T&T. Remote T&T sessions used WebEx and PathcoreScholar's online platform to discuss scoring guidelines and WSI training cases. Subsequently, external pathologists evaluated WSIs in PathcoreScholar for PD-L1 expression using either Tumor Proportion Score (TPS) or Combined Positive Score (CPS) scoring algorithms and interpreted these scores at predefined cutoffs (figure 1). In both glass and WSI scoring test modalities, passing is defined as inter and intra-observer overall agreement (OA) !85%. Training effectiveness pass rates from glass slide data (2018-2020) and WSI data (2021-2022) spanning multiple indications and scoring algorithms were calculated and then compared using the Fisher-Freeman-Halton test, with a significance threshold of 0.05. Only data from initial pathologist tests were included in the pass rate calculation; data from re-tests executed after initial test failure were excluded. Results The differences between pass rates for microscope (glass slide) and digital (WSI) testing were not statistically significant (p-value > 0.05) (tables 1 and 2). Testing pass rates for indications scored with TPS or CPS using microscope glass slide vs digital WSI T&T was not statistically significant (pvalue > 0.05) (table 3). Conclusions No statistically significant differences in pathologist training effectiveness for PD-L1 were observed between remote and in-person trainings across multiple tumor indications, scoring algorithms, and cutoffs. These results demonstrate the effectiveness and equivalency of remote-digital pathologist trainings for evaluation of PD-L1 expression as detected by PD-L1 IHC 22C3 pharmDx in multiple tumor indications when compared to in-person-microscope glass slide T&T. Use of digital training and scoring proficiency testing can provide pathologists around the world with access to high-quality, interactive training from leading experts in PD-L1 expression evaluation. Acknowledgements We would like to thank our colleagues at Agilent Technologies, Inc. and all the pathologists who completed Agilent scoring certification training and testing for their valuable contributions to this study. Tissue samples were provided by the Cooperative Human Tissue Network wh...