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Genovese, Christopher R., and Larry Wasserman. "Exceedance Control of the False Discovery Proportion." Journal of the American Statistical Association 101, no. 476 (2006): 1408–17. http://dx.doi.org/10.1198/016214506000000339.
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Dudziński, Marcin, and Konrad Furmańczyk. "A note on control of the false discovery proportion." Applicationes Mathematicae 36, no. 4 (2009): 397–418. http://dx.doi.org/10.4064/am36-4-2.
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Shang, Shulian, Qianhe Zhou, Mengling Liu, and Yongzhao Shao. "Sample Size Calculation for Controlling False Discovery Proportion." Journal of Probability and Statistics 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/817948.
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The false discovery proportion (FDP), the proportion of incorrect rejections among all rejections, is a direct measure of abundance of false positive findings in multiple testing. Many methods have been proposed to control FDP, but they are too conservative to be useful for power analysis. Study designs for controlling the mean of FDP, which is false discovery rate, have been commonly used. However, there has been little attempt to design study with direct FDP control to achieve certain level of efficiency. We provide a sample size calculation method using the variance formula of the FDP under weak-dependence assumptions to achieve the desired overall power. The relationship between design parameters and sample size is explored. The adequacy of the procedure is assessed by simulation. We illustrate the method using estimated correlations from a prostate cancer dataset.
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Goeman, Jelle J., Rosa J. Meijer, Thijmen J. P. Krebs, and Aldo Solari. "Simultaneous control of all false discovery proportions in large-scale multiple hypothesis testing." Biometrika 106, no. 4 (2019): 841–56. http://dx.doi.org/10.1093/biomet/asz041.
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Summary Closed testing procedures are classically used for familywise error rate control, but they can also be used to obtain simultaneous confidence bounds for the false discovery proportion in all subsets of the hypotheses, allowing for inference robust to post hoc selection of subsets. In this paper we investigate the special case of closed testing with Simes local tests. We construct a novel fast and exact shortcut and use it to investigate the power of this approach when the number of hypotheses goes to infinity. We show that if a minimal level of signal is present, the average power to detect false hypotheses at any desired false discovery proportion does not vanish. Additionally, we show that the confidence bounds for false discovery proportion are consistent estimators for the true false discovery proportion for every nonvanishing subset. We also show close connections between Simes-based closed testing and the procedure of Benjamini and Hochberg.
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Ge, Yongchao, and Xiaochun Li. "Control of the False Discovery Proportion for Independently Tested Null Hypotheses." Journal of Probability and Statistics 2012 (2012): 1–19. http://dx.doi.org/10.1155/2012/320425.
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Consider the multiple testing problem of testingmnull hypothesesH1,…,Hm, among whichm0hypotheses are truly null. Given theP-values for each hypothesis, the question of interest is how to combine theP-values to find out which hypotheses are false nulls and possibly to make a statistical inference onm0. Benjamini and Hochberg proposed a classical procedure that can control the false discovery rate (FDR). The FDR control is a little bit unsatisfactory in that it only concerns the expectation of the false discovery proportion (FDP). The control of the actual random variable FDP has recently drawn much attention. For any level1−α, this paper proposes a procedure to construct an upper prediction bound (UPB) for the FDP for a fixed rejection region. When1−α=50%, our procedure is very close to the classical Benjamini and Hochberg procedure. Simultaneous UPBs for all rejection regions' FDPs and the upper confidence bound for the unknownm0are presented consequently. This new proposed procedure works for finite samples and hence avoids the slow convergence problem of the asymptotic theory.
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Jeng, X. Jessie, and Xiongzhi Chen. "Predictor ranking and false discovery proportion control in high-dimensional regression." Journal of Multivariate Analysis 171 (May 2019): 163–75. http://dx.doi.org/10.1016/j.jmva.2018.12.006.
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Zhang, Xiaohua Douglas. "An Effective Method for Controlling False Discovery and False Nondiscovery Rates in Genome-Scale RNAi Screens." Journal of Biomolecular Screening 15, no. 9 (2010): 1116–22. http://dx.doi.org/10.1177/1087057110381783.
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In most genome-scale RNA interference (RNAi) screens, the ultimate goal is to select siRNAs with a large inhibition or activation effect. The selection of hits typically requires statistical control of 2 errors: false positives and false negatives. Traditional methods of controlling false positives and false negatives do not take into account the important feature in RNAi screens: many small-interfering RNAs (siRNAs) may have very small but real nonzero average effects on the measured response and thus cannot allow us to effectively control false positives and false negatives. To address for deficiencies in the application of traditional approaches in RNAi screening, the author proposes a new method for controlling false positives and false negatives in RNAi high-throughput screens. The false negatives are statistically controlled through a false-negative rate (FNR) or false nondiscovery rate (FNDR). FNR is the proportion of false negatives among all siRNAs examined, whereas FNDR is the proportion of false negatives among declared nonhits. The author also proposes new concepts, q*-value and p*-value, to control FNR and FNDR, respectively. The proposed method should have broad utility for hit selection in which one needs to control both false discovery and false nondiscovery rates in genome-scale RNAi screens in a robust manner.
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Zhang, Xiaohua Douglas, Raul Lacson, Ruojing Yang, et al. "The Use of SSMD-Based False Discovery and False Nondiscovery Rates in Genome-Scale RNAi Screens." Journal of Biomolecular Screening 15, no. 9 (2010): 1123–31. http://dx.doi.org/10.1177/1087057110381919.
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In genome-scale RNA interference (RNAi) screens, it is critical to control false positives and false negatives statistically. Traditional statistical methods for controlling false discovery and false nondiscovery rates are inappropriate for hit selection in RNAi screens because the major goal in RNAi screens is to control both the proportion of short interfering RNAs (siRNAs) with a small effect among selected hits and the proportion of siRNAs with a large effect among declared nonhits. An effective method based on strictly standardized mean difference (SSMD) has been proposed for statistically controlling false discovery rate (FDR) and false nondiscovery rate (FNDR) appropriate for RNAi screens. In this article, the authors explore the utility of the SSMD-based method for hit selection in RNAi screens. As demonstrated in 2 genome-scale RNAi screens, the SSMD-based method addresses the unmet need of controlling for the proportion of siRNAs with a small effect among selected hits, as well as controlling for the proportion of siRNAs with a large effect among declared nonhits. Furthermore, the SSMD-based method results in reasonably low FDR and FNDR for selecting inhibition or activation hits. This method works effectively and should have a broad utility for hit selection in RNAi screens with replicates.
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Hollister, Megan C., and Jeffrey D. Blume. "4497 Accessible False Discovery Rate Computation." Journal of Clinical and Translational Science 4, s1 (2020): 44. http://dx.doi.org/10.1017/cts.2020.164.
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OBJECTIVES/GOALS: To improve the implementation of FDRs in translation research. Current statistical packages are hard to use and fail to adequately convey strong assumptions. We developed a software package that allows the user to decide on assumptions and choose the hey desire. We encourage wider reporting of FDRs for observed findings. METHODS/STUDY POPULATION: We developed a user-friendly R function for computing FDRs from observed p-values. A variety of methods for FDR estimation and for FDR control are included so the user can select the approach most appropriate for their setting. Options include Efron’s Empirical Bayes FDR, Benjamini-Hochberg FDR control for multiple testing, Lindsey’s method for smoothing empirical distributions, estimation of the mixing proportion, and central matching. We illustrate the important difference between estimating the FDR for a particular finding and adjusting a hypothesis test to control the false discovery propensity. RESULTS/ANTICIPATED RESULTS: We performed a comparison of the capabilities of our new p.fdr function to the popular p.adjust function from the base stats-package. Specifically, we examined multiple examples of data coming from different unknown mixture distributions to highlight the null estimation methods p.fdr includes. The base package does not provide the optimal FDR usage nor sufficient estimation options. We also compared the step-up/step-down procedure used in adjusted p-value hypothesis test and discuss when this is inappropriate. The p.adjust function is not able to report raw-adjusted values and this will be shown in the graphical results. DISCUSSION/SIGNIFICANCE OF IMPACT: FDRs reveal the propensity for an observed result to be incorrect. FDRs should accompany observed results to help contextualize the relevance and potential impact of research findings. Our results show that previous methods are not sufficient rich or precise in their calculations. Our new package allows the user to be in control of the null estimation and step-up implementation when reporting FDRs.
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Ventura, Valérie, Christopher J. Paciorek, and James S. Risbey. "Controlling the Proportion of Falsely Rejected Hypotheses when Conducting Multiple Tests with Climatological Data." Journal of Climate 17, no. 22 (2004): 4343–56. http://dx.doi.org/10.1175/3199.1.
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Abstract The analysis of climatological data often involves statistical significance testing at many locations. While the field significance approach determines if a field as a whole is significant, a multiple testing procedure determines which particular tests are significant. Many such procedures are available, most of which control, for every test, the probability of detecting significance that does not really exist. The aim of this paper is to introduce the novel “false discovery rate” approach, which controls the false rejections in a more meaningful way. Specifically, it controls a priori the expected proportion of falsely rejected tests out of all rejected tests; additionally, the test results are more easily interpretable. The paper also investigates the best way to apply a false discovery rate (FDR) approach to spatially correlated data, which are common in climatology. The most straightforward method for controlling the FDR makes an assumption of independence between tests, while other FDR-controlling methods make less stringent assumptions. In a simulation study involving data with correlation structure similar to that of a real climatological dataset, the simple FDR method does control the proportion of falsely rejected hypotheses despite the violation of assumptions, while a more complicated method involves more computation with little gain in detecting alternative hypotheses. A very general method that makes no assumptions controls the proportion of falsely rejected hypotheses but at the cost of detecting few alternative hypotheses. Despite its unrealistic assumption, based on the simulation results, the authors suggest the use of the straightforward FDR-controlling method and provide a simple modification that increases the power to detect alternative hypotheses.
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Weller, Joel Ira, Jiu Zhou Song, David W. Heyen, Harris A. Lewin, and Micha Ron. "A New Approach to the Problem of Multiple Comparisons in the Genetic Dissection of Complex Traits." Genetics 150, no. 4 (1998): 1699–706. http://dx.doi.org/10.1093/genetics/150.4.1699.
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Abstract Saturated genetic marker maps are being used to map individual genes affecting quantitative traits. Controlling the “experimentwise” type-I error severely lowers power to detect segregating loci. For preliminary genome scans, we propose controlling the “false discovery rate,” that is, the expected proportion of true null hypotheses within the class of rejected null hypotheses. Examples are given based on a granddaughter design analysis of dairy cattle and simulated backcross populations. By controlling the false discovery rate, power to detect true effects is not dependent on the number of tests performed. If no detectable genes are segregating, controlling the false discovery rate is equivalent to controlling the experimentwise error rate. If quantitative loci are segregating in the population, statistical power is increased as compared to control of the experimentwise type-I error. The difference between the two criteria increases with the increase in the number of false null hypotheses. The false discovery rate can be controlled at the same level whether the complete genome or only part of it has been analyzed. Additional levels of contrasts, such as multiple traits or pedigrees, can be handled without the necessity of a proportional decrease in the critical test probability.
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Murray, Megan H., and Jeffrey D. Blume. "FDRestimation: Flexible False Discovery Rate Computation in R." F1000Research 10 (June 3, 2021): 441. http://dx.doi.org/10.12688/f1000research.52999.1.
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False discovery rates (FDR) are an essential component of statistical inference, representing the propensity for an observed result to be mistaken. FDR estimates should accompany observed results to help the user contextualize the relevance and potential impact of findings. This paper introduces a new user-friendly R pack-age for estimating FDRs and computing adjusted p-values for FDR control. The roles of these two quantities are often confused in practice and some software packages even report the adjusted p-values as the estimated FDRs. A key contribution of this package is that it distinguishes between these two quantities while also offering a broad array of refined algorithms for estimating them. For example, included are newly augmented methods for estimating the null proportion of findings - an important part of the FDR estimation procedure. The package is broad, encompassing a variety of adjustment methods for FDR estimation and FDR control, and includes plotting functions for easy display of results. Through extensive illustrations, we strongly encourage wider reporting of false discovery rates for observed findings.
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Murray, Megan H., and Jeffrey D. Blume. "FDRestimation: Flexible False Discovery Rate Computation in R." F1000Research 10 (October 19, 2021): 441. http://dx.doi.org/10.12688/f1000research.52999.2.
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False discovery rates (FDR) are an essential component of statistical inference, representing the propensity for an observed result to be mistaken. FDR estimates should accompany observed results to help the user contextualize the relevance and potential impact of findings. This paper introduces a new user-friendly R pack-age for estimating FDRs and computing adjusted p-values for FDR control. The roles of these two quantities are often confused in practice and some software packages even report the adjusted p-values as the estimated FDRs. A key contribution of this package is that it distinguishes between these two quantities while also offering a broad array of refined algorithms for estimating them. For example, included are newly augmented methods for estimating the null proportion of findings - an important part of the FDR estimation procedure. The package is broad, encompassing a variety of adjustment methods for FDR estimation and FDR control, and includes plotting functions for easy display of results. Through extensive illustrations, we strongly encourage wider reporting of false discovery rates for observed findings.
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Verma, Aikta, David J. Gladstone, Jiming Fang, Jordan Chenkin, Sandra E. Black, and P. Richard Verbeek. "Effect of online medical control on prehospital Code Stroke triage." CJEM 12, no. 02 (2010): 103–10. http://dx.doi.org/10.1017/s1481803500012124.
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ABSTRACT Objective: Prehospital Code Stroke triage has the potential to overwhelm stroke centres by falsely identifying patients as eligible for fibrinolysis. We sought to determine whether online medical control (whereby paramedics contact the medical control physician before a Code Stroke triage is assigned) reduced the proportion of false-positive Code Stroke patients. Methods: Following the introduction of a protocol for prehospital Code Stroke triage in an urban centre, online medical control alternated with off-line medical control (whereby paramedics implement Code Stroke triage independently) over 4 discreet intervals. We reviewed data for patients triaged to 3 regional stroke centres to compare the proportion of false-positive Code Stroke patients during online versus off-line medical control. We predefined false positives as patients triaged as Code Stroke who had symptoms discovered on awakening, were last seen in their usual state of health greater than 2 hours before assessment or had a final diagnosis other than stroke. Results: The proportion of false positives was lower during online medical control (31% v. 42%, p = 0.003). This was explained by a lower proportion of patients whose symptoms were discovered on awakening (8% v. 14%, p < 0.001) and who were last seen in their usual state of health greater than 2 hours before assessment (22% v. 32%, p = 0.005). A final diagnosis of stroke was similar in the 2 groups (77% v. 79%, p = 0.39), as was the proportion of patients receiving fibrinolysis (35% v. 33%, p = 0.72). Eighteen percent of patients were denied Code Stroke triage during online control, most commonly because of the time of symptom onset. Conclusion: Online medical control is associated with a reduced proportion of false-positive Code Stroke triage.
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Liang, Jingxuan, Xuelin Zhang, Hong Chen, Weifu Li, and Xin Tang. "Stepdown SLOPE for Controlled Feature Selection." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (2023): 8728–36. http://dx.doi.org/10.1609/aaai.v37i7.26050.
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Sorted L-One Penalized Estimation (SLOPE) has shown the nice theoretical property as well as empirical behavior recently on the false discovery rate (FDR) control of high-dimensional feature selection by adaptively imposing the non-increasing sequence of tuning parameters on the sorted L1 penalties. This paper goes beyond the previous concern limited to the FDR control by considering the stepdown-based SLOPE in order to control the probability of k or more false rejections (k-FWER) and the false discovery proportion (FDP). Two new SLOPEs, called k-SLOPE and F-SLOPE, are proposed to realize k-FWER and FDP control respectively, where the stepdown procedure is injected into the SLOPE scheme. For the proposed stepdown SLOPEs, we establish their theoretical guarantees on controlling k-FWER and FDP under the orthogonal design setting, and also provide an intuitive guideline for the choice of regularization parameter sequence in much general setting. Empirical evaluations on simulated data validate the effectiveness of our approaches on controlled feature selection and support our theoretical findings.
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Chen, Jiajie, Anthony Hou, and Thomas Y. Hou. "A pseudo knockoff filter for correlated features." Information and Inference: A Journal of the IMA 8, no. 2 (2018): 313–41. http://dx.doi.org/10.1093/imaiai/iay012.
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Abstract In Barber & Candès (2015, Ann. Statist., 43, 2055–2085), the authors introduced a new variable selection procedure called the knockoff filter to control the false discovery rate (FDR) and proved that this method achieves exact FDR control. Inspired by the work by Barber & Candès (2015, Ann. Statist., 43, 2055–2085), we propose a pseudo knockoff filter that inherits some advantages of the original knockoff filter and has more flexibility in constructing its knockoff matrix. Moreover, we perform a number of numerical experiments that seem to suggest that the pseudo knockoff filter with the half Lasso statistic has FDR control and offers more power than the original knockoff filter with the Lasso Path or the half Lasso statistic for the numerical examples that we consider in this paper. Although we cannot establish rigourous FDR control for the pseudo knockoff filter, we provide some partial analysis of the pseudo knockoff filter with the half Lasso statistic and establish a uniform false discovery proportion bound and an expectation inequality.
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Zhao, Xuebin, Hong Chen, Yingjie Wang, et al. "Error-Based Knockoffs Inference for Controlled Feature Selection." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 8 (2022): 9190–98. http://dx.doi.org/10.1609/aaai.v36i8.20905.
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Recently, the scheme of model-X knockoffs was proposed as a promising solution to address controlled feature selection under high-dimensional finite-sample settings. However, the procedure of model-X knockoffs depends heavily on the coefficient-based feature importance and only concerns the control of false discovery rate (FDR). To further improve its adaptivity and flexibility, in this paper, we propose an error-based knockoff inference method by integrating the knockoff features, the error-based feature importance statistics, and the stepdown procedure together. The proposed inference procedure does not require specifying a regression model and can handle feature selection with theoretical guarantees on controlling false discovery proportion (FDP), FDR, or k-familywise error rate (k-FWER). Empirical evaluations demonstrate the competitive performance of our approach on both simulated and real data.
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Jiang, Hongmei, and R. W. Doerge. "Estimating the Proportion of True Null Hypotheses for Multiple Comparisons." Cancer Informatics 6 (January 2008): 117693510800600. http://dx.doi.org/10.1177/117693510800600001.
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Whole genome microarray investigations (e.g. differential expression, differential methylation, ChlP-Chip) provide opportunities to test millions of features in a genome. Traditional multiple comparison procedures such as familywise error rate (FWER) controlling procedures are too conservative. Although false discovery rate (FDR) procedures have been suggested as having greater power, the control itself is not exact and depends on the proportion of true null hypotheses. Because this proportion is unknown, it has to be accurately (small bias, small variance) estimated, preferably using a simple calculation that can be made accessible to the general scientific community. We propose an easy-to-implement method and make the R code available, for estimating the proportion of true null hypotheses. This estimate has relatively small bias and small variance as demonstrated by (simulated and real data) comparing it with four existing procedures. Although presented here in the context of microarrays, this estimate is applicable for many multiple comparison situations.
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Zhijin Wu, Dongmei Liu, and Yunxia Sui. "Quantitative Assessment of Hit Detection and Confirmation in Single and Duplicate High-Throughput Screenings." Journal of Biomolecular Screening 13, no. 2 (2008): 159–67. http://dx.doi.org/10.1177/1087057107312628.
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The process of identifying active targets (hits) in high-throughput screening (HTS) usually involves 2 steps: first, removing or adjusting for systematic variation in the measurement process so that extreme values represent strong biological activity instead of systematic biases such as plate effect or edge effect and, second, choosing a meaningful cutoff on the calculated statistic to declare positive compounds. Both false-positive and false-negative errors are inevitable in this process. Common control or estimation of error rates is often based on an assumption of normal distribution of the noise. The error rates in hit detection, especially false-negative rates, are hard to verify because in most assays, only compounds selected in primary screening are followed up in confirmation experiments. In this article, the authors take advantage of a quantitative HTS experiment in which all compounds are tested 42 times over a wide range of 14 concentrations so true positives can be found through a dose-response curve. Using the activity status defined by dose curve, the authors analyzed the effect of various data-processing procedures on the sensitivity and specificity of hit detection, the control of error rate, and hit confirmation. A new summary score is proposed and demonstrated to perform well in hit detection and useful in confirmation rate estimation. In general, adjusting for positional effects is beneficial, but a robust test can prevent overadjustment. Error rates estimated based on normal assumption do not agree with actual error rates, for the tails of noise distribution deviate from normal distribution. However, false discovery rate based on empirically estimated null distribution is very close to observed false discovery proportion. ( Journal of Biomolecular Screening 2008:159-167)
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Katicha, Samer W., Daniel E. Mogrovejo, Gerardo W. Flintsch, and Edgar D. de León Izeppi. "Adaptive Spike Removal Method for High-Speed Pavement Macrotexture Measurements by Controlling the False Discovery Rate." Transportation Research Record: Journal of the Transportation Research Board 2525, no. 1 (2015): 100–110. http://dx.doi.org/10.3141/2525-11.
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Tire–pavement interactions, such as friction, tire–pavement noise, splash and spray, and rolling resistance, are significantly influenced by pavement macrotexture. Accurate texture data collection and analysis at a network level are key to achieving the desired level of safety, comfort, and sustainability of pavements. This study addressed the problem of noise in the form of spikes revealed in dynamic measurements that were performed with the use of vehicle-mounted lasers to measure macro-texture at traffic speed. The presence of spikes in collected data leads to erroneous texture measurements that do not reflect the actual pavement texture profile. As a solution to this problem, an innovative denoising methodology was developed. It consisted of an algorithm that determined the distribution of texture measurements with the use of the family of generalized Gaussian distributions, which allowed for the tail of the distribution to be heavier or thinner than the normal distribution, and with the use of the false discovery rate (FDR) method that controlled the proportion of wrongly identified spikes to all identified spikes. The FDR control allowed for an adaptive threshold selection that differentiated between valid measurements and spikes. Finally, the validation of the method showed that the mean profile depth (MPD) results obtained with denoised dynamic measurements were comparable to MPD results from the control devices on all the pavement sections investigated, making this method a significant step in the development of standardized procedures that use these devices for texture investigation at the network level.
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D'Souza, Anita, Sebastian M. Armasu, Mariza de Andrade, and John A. Heit. "Replication of Candidate Gene Single Nucleotide Polymorphisms (SNPs) Previously Reported As Associated with Venous Thromboembolism (VTE)." Blood 118, no. 21 (2011): 1238. http://dx.doi.org/10.1182/blood.v118.21.1238.1238.
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Abstract Abstract 1238 Background: SNPs within genes encoding factor XI (F11), fibrinogen genes (FGA, FGG) and other candidate genes within the procoagulant, anticoagulant, fibrinolytic, innate immunity and endocrine pathways have been reported as associated with VTE. However, the independent risk of VTE associated with many of these SNPs after controlling for factor V Leiden, Prothrombin G20210A and ABO blood group non-O carrier status is uncertain. Objective: To replicate candidate gene SNPs previously reported as associated with VTE. Methods: As part of a large replication study, we included 17 SNPs previously reported as associated with VTE in a custom Illumina Golden gate (total n=1093 SNPs) genotyping array. We genotyped 1270 non-Hispanic adults of European ancestry with objectively-diagnosed VTE (cases; no cancer, venous catheter or antiphospholipid antibodies) and 1302 controls (frequency-matched on case age, gender, race, MI/stroke status). Genotyping results from high-quality control DNA (SNP call rate ≥ 95%) was used to generate a cluster algorithm. The primary outcome was VTE status, a binary measure. The covariates were age at interview or blood sample collection, sex, stroke and/or MI status, and state of residence. To adjust for population stratification, we performed the multidimensional scaling (MDS) analysis option in PLINK v 1.07 to identify outliers in our population using the ancestry informative markers. We tested for an association between each SNP and VTE using unconditional logistic regression, adjusting for age, sex, stroke/MI status, state of residence and ABO rs514659 (in high linkage disequilibrium with non-O blood type). The analyses were corrected for multiple comparisons using an extension of false discovery rates. The false discovery rate (reported as a Q-value) is an analogue measure of the p-value that takes into account the number of statistical tests and estimates the expected proportion of false positive tests incurred when a particular SNP is significant. All analyses were performed using PLINK v 1.07. Results: MDS gave no evidence of population stratification. Genotyping was unsuccessful for two of the 17 SNPs. We found significant associations between VTE and SNPs in F11, FGG, TC2D and FGA (Table). However, the false discovery rates for all significant SNPs except F11 rs3756008 were >0.05, suggesting that the observed associations were likely falsely positive due to multiple comparisons. Even at a false discovery rate of Q-value=0.0099, one would expect ∼13 SNPs (0.0099 × 1302 SNPs) to be falsely associated with VTE due to multiple comparisons. Consequently, even our observed association between F11 rs3756008 and VTE remains tentative. Conclusions: We were unable to replicate reported associations between 15 SNPs and VTE. Our results emphasize the necessity of replication studies in different populations to confirm reported associations of SNPs with VTE. Disclosures: Heit: Daiichi Sankyo: Consultancy, Honoraria.
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Naouma, Hanaa, and Todd C. Pataky. "A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets." PeerJ 7 (December 10, 2019): e8189. http://dx.doi.org/10.7717/peerj.8189.
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Background The inflation of falsely rejected hypotheses associated with multiple hypothesis testing is seen as a threat to the knowledge base in the scientific literature. One of the most recently developed statistical constructs to deal with this problem is the false discovery rate (FDR), which aims to control the proportion of the falsely rejected null hypotheses among those that are rejected. FDR has been applied to a variety of problems, especially for the analysis of 3-D brain images in the field of Neuroimaging, where the predominant form of statistical inference involves the more conventional control of false positives, through Gaussian random field theory (RFT). In this study we considered FDR and RFT as alternative methods for handling multiple testing in the analysis of 1-D continuum data. The field of biomechanics has recently adopted RFT, but to our knowledge FDR has not previously been used to analyze 1-D biomechanical data, nor has there been a consideration of how FDR vs. RFT can affect biomechanical interpretations. Methods We reanalyzed a variety of publicly available experimental datasets to understand the characteristics which contribute to the convergence and divergence of RFT and FDR results. We also ran a variety of numerical simulations involving smooth, random Gaussian 1-D data, with and without true signal, to provide complementary explanations for the experimental results. Results Our results suggest that RFT and FDR thresholds (the critical test statistic value used to judge statistical significance) were qualitatively identical for many experimental datasets, but were highly dissimilar for others, involving non-trivial changes in data interpretation. Simulation results clarified that RFT and FDR thresholds converge as the true signal weakens and diverge when the signal is broad in terms of the proportion of the continuum size it occupies. Results also showed that, while sample size affected the relation between RFT and FDR results for small sample sizes (<15), this relation was stable for larger sample sizes, wherein only the nature of the true signal was important. Discussion RFT and FDR thresholds are both computationally efficient because both are parametric, but only FDR has the ability to adapt to the signal features of particular datasets, wherein the threshold lowers with signal strength for a gain in sensitivity. Additional advantages and limitations of these two techniques as discussed further. This article is accompanied by freely available software for implementing FDR analyses involving 1-D data and scripts to replicate our results.
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Crager, M. R., and S. Shak. "Are more genes better in clinical-genomic studies? A mathematical model to define identification power for clinically relevant genes." Journal of Clinical Oncology 27, no. 15_suppl (2009): e22136-e22136. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e22136.
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e22136 Background: Modern molecular technologies that drive personalized medicine can generate expression data for thousands of candidate genes, or indeed, data for the “whole genome”. Clinical-genomic studies aim to identify genes that are truly associated with clinical outcome. We investigated the impact of large numbers of genes with little or no association with clinical outcome on the statistical power of studies to identify individual genes with strong association. Methods: We adapted Efron's (Ann Stat 2007) empirical Bayes approach to develop a method to calculate the identification power for individual genes in analyses that control the false discovery rate (FDR), the expected proportion of false positives. The identification power is the probability that a gene with a given true magnitude of association with clinical outcome will be identified when we control the FDR at a specified level. The identification power also depends on the proportion of genes studied that are not associated with outcome and the distribution of the degree of association among genes that are. Results: The identification power for clinically relevant genes decreases dramatically as the proportion of genes having no association with clinical outcome increases. For example, in a scenario in which 100 genes have some association with clinical outcome [median hazard ratio (HR) 1.125], increasing the number of genes having no association from 400 to 4000 decreases the identification power an individual gene having strong association (HR 1.42) from 80% to 36%. Similarly, when the number of genes having no association is 400 and the median HR among the 100 genes that have an association is decreased from 1.125 to 1.06, identification power for a gene with an association HR of 1.42 decreases from 80% to 62%. Conclusions: Identification power can be used to optimize strategies for gene finding and enable personalized medicine. Although technology allows the assay of ever-increasing numbers of genes, inclusion in a single study of many genes unrelated to clinical outcome is detrimental to the identification power for clinically relevant genes. Even with increased power, replication of results in independent studies will continue to be critically important. [Table: see text]
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Cheng, Cheng, Stanley B. Pounds, James M. Boyett, Deqing Pei, Mei-Ling Kuo, and Martine F. Roussel. "Statistical Significance Threshold Criteria For Analysis of Microarray Gene Expression Data." Statistical Applications in Genetics and Molecular Biology 3, no. 1 (2004): 1–30. http://dx.doi.org/10.2202/1544-6115.1064.
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The methodological advancement in microarray data analysis on the basis of false discovery rate (FDR) control, such as the q-value plots, allows the investigator to examine the FDR from several perspectives. However, when FDR control at the “customary" levels 0.01, 0.05, or 0.1 does not provide fruitful findings, there is little guidance for making the trade off between the significance threshold and the FDR level by sound statistical or biological considerations. Thus, meaningful statistical significance criteria that complement the existing FDR methods for large-scale multiple tests are desirable. Three statistical significance criteria, the profile information criterion, the total error proportion, and the guide-gene driven selection, are developed in this research. The first two are general significance threshold criteria for large-scale multiple tests; the profile information criterion is related to the recent theoretical studies of the connection between FDR control and minimax estimation, and the total error proportion is closely related to the asymptotic properties of FDR control in terms of the total error risk. The guide-gene driven selection is an approach to combining statistical significance and the existing biological knowledge of the study at hand. Error properties of these criteria are investigated theoretically and by simulation. The proposed methods are illustrated and compared using an example of genomic screening for novel Arf gene targets. Operating characteristics of q-value and the proposed significance threshold criteria are investigated and compared in a simulation study that employs a model mimicking a gene regulatory pathway. A guideline for using these criteria is provided. Splus/R code is available from the corresponding author upon request.
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Carlsen, Louise Ninett, Christine Søholm Hansen, Lisette J. A. Kogelman, et al. "DNA-methylation and immunological response in medication overuse headache." Cephalalgia 43, no. 3 (2023): 033310242211474. http://dx.doi.org/10.1177/03331024221147482.
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Objective To investigate whether medication-overuse headache patients have differential DNA-methylation pattern. Methods We collected blood samples from 120 medication-overuse headache-patients, 57 controls (29 episodic migraine patients and 28 healthy controls) in a hypothesis-generating cross-sectional case-control pilot study; 100 of the medication-overuse headache-patients were followed for six months and samples were collected at two and six months for the longitudinal methylation analyses. Blood cell proportions of leucocytes (neutrophils, NK-cells, monocytes, CD8+ and CD4+ T-cells, and B-cells) and the neutrophile-lymphocyte ratio were estimated using methylation data as a measure for immunological analysis and a cell type-specific epigenome wide association study was conducted between medication-overuse headache-patients and controls, and longitudinally for reduction in headache days/month among medication-overuse headache-patients. Results We found a higher neutrophile-lymphocyte ratio in medication-overuse headache-patients compared to controls, indicating a higher immunological response in medication-overuse headache-patients (false discovery rate (adjusted p-value)<0.001). Reduction in headache days/month (9.8; 95% CI 8.1–11.5) was associated with lower neutrophile-lymphocyte ratio (false discovery rate adjusted p-value = 0.041). Three genes ( CORIN, CCKBR and CLDN9) were hypermethylated in specific cell types in medication-overuse headache-patients compared to controls. No methylation differences were associated with reduction in headache days in medication-overuse headache-patients after six months. Conclusion This pilot study was consistent with higher immunological response in medication-overuse headache-patients which decreased with a reduction in headache days in longitudinal analysis. medication-overuse headache-patients exhibited differential methylation in innate immune cells but did not exhibit longitudinal differences with alterations in headache days. Our study creates hypotheses for further biomarker searches. ClinicalTrials.gov Identifier: NCT02993289
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Choi, Seong Ji, Hyuk Soon Choi, Hyunil Kim, et al. "Gastric Cancer and Intestinal Metaplasia: Differential Metabolic Landscapes and New Pathways to Diagnosis." International Journal of Molecular Sciences 25, no. 17 (2024): 9509. http://dx.doi.org/10.3390/ijms25179509.
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Gastric cancer (GC) is the fifth most common cause of cancer-related death worldwide. Early detection is crucial for improving survival rates and treatment outcomes. However, accurate GC-specific biomarkers remain unknown. This study aimed to identify the metabolic differences between intestinal metaplasia (IM) and GC to determine the pathways involved in GC. A metabolic analysis of IM and tissue samples from 37 patients with GC was conducted using ultra-performance liquid chromatography with tandem mass spectrometry. Overall, 665 and 278 significant features were identified in the aqueous and 278 organic phases, respectively, using false discovery rate analysis, which controls the expected proportion of false positives among the significant results. sPLS-DA revealed a clear separation between IM and GC samples. Steroid hormone biosynthesis, tryptophan metabolism, purine metabolism, and arginine and proline metabolism were the most significantly altered pathways. The intensity of 11 metabolites, including N1, N2-diacetylspermine, creatine riboside, and N-formylkynurenine, showed significant elevation in more advanced GC. Based on pathway enrichment analysis and cancer stage-specific alterations, we identified six potential candidates as diagnostic biomarkers: aldosterone, N-formylkynurenine, guanosine triphosphate, arginine, S-adenosylmethioninamine, and creatine riboside. These metabolic differences between IM and GC provide valuable insights into gastric carcinogenesis. Further validation is needed to develop noninvasive diagnostic tools and targeted therapies to improve the outcomes of patients with GC.
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Yavuz, Hande. "Predictive modeling of material properties for aircraft control cables." Aircraft Engineering and Aerospace Technology 92, no. 10 (2020): 1533–38. http://dx.doi.org/10.1108/aeat-05-2020-0103.
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Purpose This study aims to investigate the relationship between material properties and alloying elements of carbon steels through predictive modeling. Aircraft control cables are usually made of steel materials and subjected to deformation because of the motion of control surfaces such as aileron, rudder, elevator and trailing edge flaps. Investigation of the relationship between material properties and alloying elements would therefore be explored. Design/methodology/approach This study is focused on the modeling of mechanical properties of carbon steels concerning the content of alloying elements by using response surface methodology with false discovery rate (FDR) correction approach. SAS Institute JMP data analysis software was used to develop response and argument relationships in various carbon steels without including thermomechanical treatment effect. Mechanical properties were considered as tensile strength, yield strength, ductility, and Brinell hardness. Carbon (0.28 Wt.%-0.46 Wt.%) and manganese (0.7 Wt.%-0.9 Wt.%) proportions were gathered from ASM Handbook. Linear regression models were tested for the statistical adequacy by using analysis of variance and statistical significance analysis. A posterior probability, which refers to Benjamini–Hochberg FDR (BH-FDR), was embedded as multiple testing corrections of the t-test p-values. Findings Predictive modeling of the material properties for aircraft control cables was successfully achieved by using the response surface method with BH-FDR significance level of 0.05. Originality/value The effect of statistically developed graphical interactions of alloying elements on the common mechanical properties of such steels would provide prompt comparison to material suppliers and part manufacturers except those subjected to thermomechanical treatment applications.
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Vilibic-Cavlek, Tatjana, Maja Bogdanic, Ema Borko, et al. "Detection of SARS-CoV-2 Antibodies: Comparison of Enzyme Immunoassay, Surrogate Neutralization and Virus Neutralization Test." Antibodies 12, no. 2 (2023): 35. http://dx.doi.org/10.3390/antib12020035.
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Background: Since sensitivity and specificity vary widely between tests, SARS-CoV-2 serology results should be interpreted with caution. Methods: The study included serum samples from patients who had recovered from COVID-19 (n = 71), individuals vaccinated against SARS-CoV-2 (n = 84), and asymptomatic individuals (n = 33). All samples were tested for the presence of binding antibodies (enzyme immunoassay; EIA), neutralizing (NT) antibodies (virus neutralization test; VNT), and surrogate NT (sNT) antibodies (surrogate virus neutralization test; sVNT) of SARS-CoV-2. Results: SARS-CoV-2-binding antibodies were detected in 71 (100%) COVID-19 patients, 77 (91.6%) vaccinated individuals, and 4 (12.1%) control subjects. Among EIA-positive samples, VNT was positive (titer ≥ 8) in 100% of COVID-19 patients and 63 (75.0%) of the vaccinated individuals, while sVNT was positive (>30% inhibition) in 62 (87.3%) patients and 59 (70.2%) vaccinated individuals. The analysis of antibody levels showed a significant moderate positive correlation between EIA and VNT, a moderate positive correlation between EIA and sVNT, and a strong positive correlation between VNT and sVNT. The proportion of positive sVNT detection rate was associated with VNT titer. The lowest positivity (72.4%/70.8%) was detected in samples with low NT titers (8/16) and increased progressively from 88.2% in samples with titer 32 to 100% in samples with titer 256. Conclusions: sVNT appeared to be a reliable method for the assessment COVID-19 serology in patients with high antibody levels, while false-negative results were frequently observed in patients with low NT titers.
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Bruckert, Lisa, Katie Travis, Emily McKenna, Kristen Yeom, and Cynthia Campen. "NFB-11. WHITE MATTER DIFFERENCES IN CHILDREN WITH NF1 COMPARED TO CONTROLS." Neuro-Oncology 22, Supplement_3 (2020): iii419—iii420. http://dx.doi.org/10.1093/neuonc/noaa222.614.
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Abstract INTRODUCTION Neurofibromatosis type 1 (NF1) is a genetic condition in which children develop learning challenges and glioma. White matter tracts (WMT) are implicated in these cognitive functions, while oligodendroglial precursor cells are implicated in both gliomagenesis and white-matter development. Specific WMTs have not been well characterized in NF1. METHODS Twenty NF1 patients aged 1.4–17.6 years (M = 9.5 years, 24 male) and 20 age-and-sex-matched controls underwent dMRI at 3T (25 directions, b=1000 s/mm2). Automated segmentation of WMTs extracted fractional anisotropy (FA) and mean diffusivity (MD) of 18 major WMTs. Covariance analysis examined the effect of group (NF1/controls) on FA/MD after controlling for intracranial volume. Regression analyses for WMTs determined the interaction of FA/MD with age for NF1 patients compared to controls. Significance was set at p&lt;0.05 after correcting for multiple comparisons using false discovery rate. RESULTS Compared to controls, children with NF1 had significantly decreased FA in 8 and increased MD in 12/18 tracts. Differences held after controlling for intracranial volume. The interaction between group and age accounted for a significant proportion of the variance in FA in 9 and in MD in 16/18 tracts. FA and MD differences between children with NF1 and controls were greater at younger than older ages. CONCLUSION Microstructural differences were observed in WMTs in children with NF1 compared to controls. These differences were not explained by intracranial volume and were most pronounced in younger children with NF1 compared to controls. These findings have implications for understanding neurocognitive deficits and gliomagenesis observed in children with NF1.
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Čerina, Dora, Višnja Matković, Kristina Katić, et al. "Real-World Efficacy and Safety of Bevacizumab in the First-Line Treatment of Metastatic Cervical Cancer: A Cohort Study in the Total Population of Croatian Patients." Journal of Oncology 2021 (August 5, 2021): 1–8. http://dx.doi.org/10.1155/2021/2815623.
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Background. Although today it is almost preventable, cervical cancer still represents a significant cancer burden, especially in some developing parts of the world. Since the introduction of bevacizumab in the first-line treatment of metastatic disease, improvements of the outcomes were noted. However, results from randomized controlled trials are often hard to recreate in the real-world setting. Objective. To assess the real-world efficacy and safety of bevacizumab as a first-line treatment of advanced cervical cancer. Methods. We conducted a retrospective cohort study on the total population of Croatian patients diagnosed with metastatic cervical cancer from 2016 to 2019 who were treated with bevacizumab in combination with cisplatin and paclitaxel (TCB) in the first line. The comparison group was the consecutive sample of patients treated with chemotherapy alone. The primary endpoint was overall survival (OS). Secondary endpoints were progression-free survival (PFS), objective response rate, incidence of adverse events, and the proportion of treatment discontinuation. Results. We enrolled 67 patients treated with TCB and a control group of 62 patients treated with chemotherapy alone. The TCB cohort had significantly longer unadjusted OS with a median of 27.0 (95% CI 18.5; not calculable) months, compared to 15.5 (10.7; 30.1) months in the chemotherapy-alone cohort. Adjusted OS was not significantly different. PFS was significantly longer for the TCB cohort, with a median of 10.6 (95% CI 8.5; 15.4) months, than for the chemotherapy-alone cohort, with a median of 5.4 (95% CI 3.9; 9.1) months, even after adjustment for baseline covariates (HRadjusted = 0.60; 95% CI 0.39; 0.94; p = 0.027 ; false discovery rate <5%). Conclusions. In a real-world setting, TCB as a first-line treatment of metastatic cervical cancer was associated with longer PFS, better objective disease control rate, and acceptable toxicity profile in comparison to chemotherapy alone. These results may indicate its utility and potential applicability in other parts of the developing world.
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Kan, Hui, Yining He, Qing Li, et al. "Differential Effect of Vaginal Microbiota on Spontaneous Preterm Birth among Chinese Pregnant Women." BioMed Research International 2022 (December 1, 2022): 1–12. http://dx.doi.org/10.1155/2022/3536108.
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Objective. The effect of vaginal microbiota on spontaneous preterm birth (sPTB) has not been fully addressed, and few studies have explored the associations between vaginal taxa and sPTB in the gestational diabetes mellitus (GDM) and non-GDM groups, respectively. Study Design. To minimize external interference, a total of 41 pregnant women with sPTB and 308 controls (pregnant women without sPTB) from same regain were enrolled in this case-cohort study. Controls were randomly selected at baseline. With the exception of GDM, other characteristics were not significantly different between the two groups. Vaginal swabs were collected at early second trimester. Using 16S amplicon sequencing, the main bioinformatics analysis was performed on the platform of QIIME 2. Vaginal microbiota traits of the sPTB group were compared with controls. Finally, the effects of binary taxa on sPTB in the GDM group and the non-GDM group were analyzed, respectively. Results. The proportion of GDM in the sPTB (19.51%) was higher than the controls (7.47%, P = 0.018 ). The vaginal microbiota of pregnant women with sPTB exhibited higher alpha diversity metrics (observed features, P = 0.001 ; Faith’s phylogenetic diversity, P = 0.013 ) and different beta diversity metrics (unweighted UniFrac, P = 0.006 ; Jaccard’s distance, P = 0.004 ), compared with controls. The presence of Lactobacillus paragasseri/gasseri (aOR: 3.12, 95% CI: 1.24-7.84), Streptococcus (aOR: 3.58, 95% CI: 1.68-7.65), or Proteobacteria (aOR: 3.39, 95% CI: 1.55-7.39) was associated with an increased risk of sPTB in the non-GDM group ( P < 0.05 ). However, the relative abundance of novel L. mulieris (a new species of the L. delbrueckii group) was associated with a decreased risk of sPTB (false discovery rate, 0.10) in all pregnant women. Conclusion. GDM may modify the association of vaginal taxa with sPTB, suggesting that maternal GDM should be considered when using vaginal taxa to identify pregnant women at high risk of sPTB.
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Scherer, Dominique, Heike Deutelmoser, Yesilda Balavarca, et al. "Polymorphisms in the Angiogenesis-Related Genes EFNB2, MMP2 and JAG1 Are Associated with Survival of Colorectal Cancer Patients." International Journal of Molecular Sciences 21, no. 15 (2020): 5395. http://dx.doi.org/10.3390/ijms21155395.
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An individual’s inherited genetic variation may contribute to the ‘angiogenic switch’, which is essential for blood supply and tumor growth of microscopic and macroscopic tumors. Polymorphisms in angiogenesis-related genes potentially predispose to colorectal cancer (CRC) or affect the survival of CRC patients. We investigated the association of 392 single nucleotide polymorphisms (SNPs) in 33 angiogenesis-related genes with CRC risk and survival of CRC patients in 1754 CRC cases and 1781 healthy controls within DACHS (Darmkrebs: Chancen der Verhütung durch Screening), a German population-based case-control study. Odds ratios and 95% confidence intervals (CI) were estimated from unconditional logistic regression to test for genetic associations with CRC risk. The Cox proportional hazard model was used to estimate hazard ratios (HR) and 95% CIs for survival. Multiple testing was adjusted for by a false discovery rate. No variant was associated with CRC risk. Variants in EFNB2, MMP2 and JAG1 were significantly associated with overall survival. The association of the EFNB2 tagging SNP rs9520090 (p < 0.0001) was confirmed in two validation datasets (p-values: 0.01 and 0.05). The associations of the tagging SNPs rs6040062 in JAG1 (p-value 0.0003) and rs2241145 in MMP2 (p-value 0.0005) showed the same direction of association with overall survival in the first and second validation sets, respectively, although they did not reach significance (p-values: 0.09 and 0.25, respectively). EFNB2, MMP2 and JAG1 are known for their functional role in angiogenesis and the present study points to novel evidence for the impact of angiogenesis-related genetic variants on the CRC outcome.
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Shah, Mithun V., Rakchha Chhetri, Urshila Durani, et al. "T-MDS Is a Distinct Clinical and Pathological Entity Characterized By Better Survival Compared to t-AML." Blood 138, Supplement 1 (2021): 3377. http://dx.doi.org/10.1182/blood-2021-152380.
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Abstract Introduction: Therapy-related myeloid neoplasm (t-MN) includes acute myeloid leukemia (AML), myelodysplastic syndrome (MDS), and myelodysplastic/myeloproliferative neoplasms (MDS/MPN) that occur as a complication of DNA-damaging therapies. The World Health Organization recommends considering t-MN as a single entity. Whether t-MDS and t-AML have distinct characteristics and outcomes is not known. The aim of this study was to compare clinicopathological characteristics and outcomes of t-MDS and t-AML. Methods: All patients diagnosed with t-MN based on the World Health Organization criteria were identified. Bone marrow biopsies, cytogenetic, and next-generation sequencing (NGS) were obtained at the treating physician's discretion. Pathogenic/likely pathogenic variants (PV) were called based on the standard criteria. Overall survival (OS) was calculated from the time of t-MN diagnosis until the last follow up using Kaplan-Meier analysis using Wilcoxon test. For survival analysis comparing chemotherapy to best supportive care (BSC) only, patients were censored at the time of allogeneic stem cell transplant (SCT). Multivariate analysis was performed using Cox proportional hazard method and corrected using false discovery rate (FDR). Statistical analysis was performed using JMP (v14.1, SAS Institute) and significance was defined as P&lt;0.05. Results: We identified 554 patients, of which 180 (32.4%), 365 (65.8%), and 9 (1.6%) presented as t-AML, t-MDS, and t-MDS/MPN respectively. t-MDS/MPN patients were excluded from further analysis due to a small number. Clinical and laboratory characteristics of the t-AML and t-MDS cohorts is shown in Table 1. t-AML patients were significantly more anemic and thrombocytopenic at presentation. As expected, t-AML had a higher peripheral blood and BM blast count. There was no difference in proportion of patients with chromosomal abnormalities, though a statistically significantly higher proportion of t-MDS patients had chromosome 5 abnormality, 5q deletion, monosomy 5, chromosome 7 abnormality, monosomy 7 compared to t-AML patients. On other hand, 11q23 (mixed lineage leukemia, MLL) rearrangement was more common in t-AML compared to t-MDS (9.3% vs. 2.8%, P=0.005). A higher proportion of t-MDS patients had PV detected by NGS compared to t-AML (92.9% vs. 85.6%, P=0.038). A higher proportion of t-MDS patients had PV in TP53 (37.6% vs. 21.4%, P=0.004) and ASXL1 (23% vs. 11.7%, P=0.016) genes; whereas a higher proportion of t-AML patients had PV in RAS (18.9% vs. 9.1%, P=0.013) and WT1 (8.1% vs. 2.9%, P=0.05) genes. One hundred twenty-eight (35%) of 365 t-MDS patients progressed to t-AML. The presence of any chromosomal abnormality at t-MDS diagnosis predicted a higher risk of transformation to t-AML (χ 2 3.9, P=0.03). t-AML patients had a significantly shorter OS compared to t-MDS (9.2 vs. 19.7 months, P&lt;0.0001, Figure A). This difference persisted when stratified by no disease modifying therapies (BSC only) 2 vs. 17 months (P&lt;0.0001, Figure B), as well as among those who received at least one line of chemotherapy (14 vs. 24.6 months, P&lt;0.001). Finally, a higher proportion of patients with t-AML underwent SCT and there was a trend towards improved survival for t-AML patients (vs. t-MDS 52.9 vs. 20.7 months, P=0.07) from the time of transplant. Multivariate analysis for OS performed to control for all the variables that were different at presentation (except for blast count), showed that t-MDS (as opposed to t-AML) phenotype at diagnosis, and undergoing SCT were independent predictors of improved survival (Table 2). Conclusion: t-MDS and t-AML have distinct clinical, cytogenetic, and genetic features at presentation. In the absence of disease modifying therapies, t-AML is a more aggressive phenotype, consistently associated with a shorter survival. Even after controlling adverse risk features, t-AML phenotype had a shorter survival compared to t-MDS. Figure 1 Figure 1. Disclosures Litzow: AbbVie: Research Funding; Astellas: Research Funding; Amgen: Research Funding; Actinium: Research Funding; Pluristem: Research Funding; Jazz: Other: Advisory Board; Omeros: Other: Advisory Board; Biosight: Other: Data monitoring committee. Hiwase: Novartis: Membership on an entity's Board of Directors or advisory committees; AbbVie: Membership on an entity's Board of Directors or advisory committees.
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Zamani, Shawn A., Kathleen M. McClain, Barry I. Graubard, et al. "Dietary Polyunsaturated Fat Intake in Relation to Head and Neck, Esophageal, and Gastric Cancer Incidence in the National Institutes of Health–AARP Diet and Health Study." American Journal of Epidemiology 189, no. 10 (2020): 1096–113. http://dx.doi.org/10.1093/aje/kwaa024.
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Abstract Recent epidemiologic studies have examined the association of fish consumption with upper gastrointestinal cancer risk, but the associations with n-3 and n-6 polyunsaturated fatty acid (PUFA) subtypes remain unclear. Using the National Institutes of Health–AARP Diet and Health Study (United States, 1995–2011), we prospectively investigated the associations of PUFA subtypes, ratios, and fish with the incidence of head and neck cancer (HNC; n = 2,453), esophageal adenocarcinoma (EA; n = 855), esophageal squamous cell carcinoma (n = 267), and gastric cancer (cardia: n = 603; noncardia: n = 631) among 468,952 participants (median follow-up, 15.5 years). A food frequency questionnaire assessed diet. Multivariable-adjusted hazard ratios were estimated using Cox proportional hazards regression. A Benjamini-Hochberg (BH) procedure was used for false-discovery control. Long-chain n-3 PUFAs were associated with a 20% decreased HNC and EA risk (for HNC, quintile5 vs. 1 hazard ratio = 0.81, 95% confidence interval: 0.71, 0.92, and BH-adjusted Ptrend = 0.001; and for EA, quintile5 vs. 1 hazard ratio = 0.79, 95% confidence interval: 0.64, 0.98, and BH-adjusted Ptrend = 0.1). Similar associations were observed for nonfried fish but only for high intake. Further, the ratio of long-chain n-3:n-6 was associated with a decreased HNC and EA risk. No consistent associations were observed for gastric cancer. Our results indicate that dietary long-chain n-3 PUFA and nonfried fish intake are associated with lower HNC and EA risk.
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Ghosal, Subhashis, and Anindya Roy. "Predicting False Discovery Proportion Under Dependence." Journal of the American Statistical Association 106, no. 495 (2011): 1208–18. http://dx.doi.org/10.1198/jasa.2011.tm10488.
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Mefford, Joel A., Zilong Zhao, Leah Heilier, et al. "Varied performance of picture description task as a screening tool across MCI subtypes." PLOS Digital Health 2, no. 3 (2023): e0000197. http://dx.doi.org/10.1371/journal.pdig.0000197.
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A picture description task is a component of Miro Health’s platform for self-administration of neurobehavioral assessments. Picture description has been used as a screening tool for identification of individuals with Alzheimer’s disease and mild cognitive impairment (MCI), but currently requires in-person administration and scoring by someone with access to and familiarity with a scoring rubric. The Miro Health implementation allows broader use of this assessment through self-administration and automated processing, analysis, and scoring to deliver clinically useful quantifications of the users’ speech production, vocal characteristics, and language. Picture description responses were collected from 62 healthy controls (HC), and 33 participants with MCI: 18 with amnestic MCI (aMCI) and 15 with non-amnestic MCI (naMCI). Speech and language features and contrasts between pairs of features were evaluated for differences in their distributions in the participant subgroups. Picture description features were selected and combined using penalized logistic regression to form risk scores for classification of HC versus MCI as well as HC versus specific MCI subtypes. A picture-description based risk score distinguishes MCI and HC with an area under the receiver operator curve (AUROC) of 0.74. When contrasting specific subtypes of MCI and HC, the classifiers have an AUROC of 0.88 for aMCI versus HC and and AUROC of 0.61 for naMCI versus HC. Tests of association of individual features or contrasts of pairs of features with HC versus aMCI identified 20 features with p-values below 5e-3 and False Discovery Rates (FDRs) at or below 0.113, and 61 contrasts with p-values below 5e-4 and FDRs at or below 0.132. Findings suggest that performance of picture description as a screening tool for MCI detection will vary greatly by MCI subtype or by the proportion of various subtypes in an undifferentiated MCI population.
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Fernández Aceñero, M. Jesús, M. Vázquez, J. M. Esteban, Guillermo García Diego, and Cristina Díaz del Arco. "Influence of the Histopathological Features of the Lesion on the Diagnostic Yield of Fine-Needle Aspiration Cytology of Pancreatic Solid Lesions." Acta Cytologica 62, no. 4 (2018): 259–64. http://dx.doi.org/10.1159/000488383.
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Objective: The rate of pancreatic lesions has increased in recent decades due to the widespread use of advanced imaging techniques. Nowadays, a significant proportion of cases are incidentally discovered in asymptomatic patients and cytology is an important tool for the diagnosis and multidisciplinary management of these cases. Study Design: In this study we retrospectively review the experience with pancreatic fine-needle aspiration cytology in the last 17 years at a single large tertiary hospital in Madrid, Spain. Results: Our results indicate that more than 60% of pancreatic malignant lesions are cytologically confirmed before surgery and 30% of the patients are asymptomatic. Despite this, we have noted that the total number of malignant lesions surgically resected in our hospital has basically remained unchanged over the years, because incidental diagnosis is not always synonymous with resectability and a substantial number of patients are already metastatic at the time of diagnosis. Our series also shows an increase in the number of neuroendocrine tumors, which now represent almost 20% of all cytological diagnoses at our hospital. The sensitivity in our series is 70% and the false negative rate remains 30%, despite sample quality control by experienced cytologists and standardized technical conditions. Fibrosis and necrosis are the 2 features of the primary tumor that significantly and negatively influence the accuracy of cytologic diagnosis. Conclusion: We herein report our experience with cytologic diagnosis of pancreatic lesions in a single tertiary hospital. Our results confirm that cytology is a safe, reliable, and important tool for pancreatic lesion diagnosis and management.
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Loureiro, B., L. Oliveira, and P. J. Hansen. "244 CHANGES IN THE TRANSCRIPTOME OF THE BOVINE PRE-IMPLANTATION EMBRYO INDUCED BY COLONY-STIMULATING FACTOR-2." Reproduction, Fertility and Development 22, no. 1 (2010): 279. http://dx.doi.org/10.1071/rdv22n1ab244.
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Colony-stimulating factor-2 (CSF-2) is a cytokine expressed in bovine oviduct and endometrium that has been reported to improve the proportion of embryos that become blastocysts in vitro and survive after transfer to recipients. One effect of CSF-2 that might be related to increased embryonic survival is a preferential increase in the number of cells in the inner cell mass. The objective of the current study was to determine changes in the embryo transcriptome caused by CSF-2 that promote blastocyst formation and establishment and maintenance of pregnancy after transfer. Bovine embryos were produced in vitro and cultured in KSOM-BE2 +10 ng/mL recombinant BoCSF-2 added at Day 5 after insemination. On Day 6 (24 h after treatment), embryos at the morula and early blastocyst stage were harvested and stored in groups of 50 at -80°C. A total of 4 pools of GM-colony-stimulating factor treated blastocysts and 4 control blastocysts were subjected to transcriptional profiling using the Bos taurus 2-color Agilent chip (4 × 44 K format). Before labeling, total RNA starting sample was spiked with control genes (artificial clones) of known concentration provided by Agilent. Labeling was done simultaneously with complimentary RNA (cRNA) amplification. Two rounds of linear RNA amplification were employed. Images were extracted using the Agilent Feature Extraction Software (Agilent Technologies, Santa Clara, CA, USA) and normalized within arrays by the Lowess method. Statistical analysis was performed using the JMP Genomics program (SAS Inst., Cary, NC, USA). The normalized data were log2 transformed, and the quantile normalization method was used to normalize data between arrays. Differences in gene expression were determined using PROC ANOVA (fixed false discovery rate = 0.01). Only genes with a 1.5-fold difference and P < 0.05 were considered differentially expressed. A total of 216 genes were differentially expressed between CSF-2 and control embryos. Of these, 141 could be annotated (61 genes up-regulated and 80 genes down-regulated by CSF-2). These included 13 genes involved in Wnt pathways, including 5 inhibitors of Wnt signaling (FRP, MAB21L2, PCDH24, PDE7, PPPR23A) that were up-regulated by CSF-2 and 5 genes involved in transmission of Wnt signals (WNT16, ROR2, CSNK2B, CELSR2, DTX3) that were down-regulated by CSF-2. Several other genes associated with differentiation were down-regulated by CSF-2 including CXCL12, FEZF1, PLD2, and RGS12. Expression of 1 gene that inhibits apoptosis (PRKAR2B) was increased by CSF-2, whereas expression of 6 genes involved in apoptosis pathways (DAPK1, MADD, NOD2, PIK3IP1, RIPK3, RNF7) were down-regulated. Results indicate that CSF-2 promotes pluripotency and decreases apoptosis in bovine pre-implantation embryos. This research was supported by USDA-AFRI. B. Loureiro andL. Oliveira were supported by a CAPES (Brazil)/Fulbright Fellowship.
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Merchan, Jaime R., Woo Kyun Bae, Chan Kim, et al. "Correlation of distinct circulating cytokine/chemokine profiles with clinical benefits of Pexa-Vec (thymidine kinase-deactivated vaccinia virus plus GM-CSF) and cemiplimab (REGN2810; anti-PD-1) in metastatic or unresectable renal cell carcinoma (mRCC)." Journal of Clinical Oncology 42, no. 16_suppl (2024): e14539-e14539. http://dx.doi.org/10.1200/jco.2024.42.16_suppl.e14539.
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e14539 Background: This study explores the transformation of 'cold' tumour microenvironments into 'hot' ones in mRCC, focusing on the potential of Oncolytic Viruses (OVs) for personalized immunotherapy. Recognizing the variability in patient responses, the research underscores the necessity for reliable biomarkers. The objective is to examine the correlation between plasma cytokine/chemokine levels and the efficacy of Pexa-Vec and cemiplimab, proposing that these biomarkers could predict treatment outcomes and contribute to more personalized cancer treatment protocols. Methods: In this study, mRCC patients from the REN026 trial were categorized into three treatment groups: Pexa-Vec (Intratumoral and intravenous) and cemiplimab combination therapy (N=65), intravenous Pexa-Vec and cemiplimab combination therapy (N=54), and cemiplimab monotherapy (N=14). Blood samples were collected at baseline, during treatment, and at end of treatment (EOT) for analysis. Subsequently, the plasma samples underwent analysis using the Human Cytokine 96-Plex Discovery Assay through the Luminex 200 system. The statistical approach included the Mann–Whitney U-test or Wilcoxon signed-rank test, along with a Cox proportional hazards model. The False Discovery Rate (FDR) method was employed to control type I error. Results: During the follow-up period from June 2018 to February 2023, key outcomes were observed as follows (Table): In the Pexa-Vec and cemiplimab cohort, a lower baseline of MCP-3 or an increased rate of change in post-treatment levels of IFNβ, Eotaxin, IL-1α, and sFasL were associated with improved Progression-Free Survival (PFS). Specifically, a low baseline of MCP-3 or an increased level of Eotaxin and sFasL post-treatment correlated with enhanced Overall Survival (OS). In the intravenous Pexa-Vec and cemiplimab group, a rise in post-treatment levels of IFNβ, Eotaxin, IL-17F, and sFasL were indicative of better PFS, with elevated Eotaxin also suggesting improved OS. Within the cemiplimab monotherapy group, an increase in post-treatment IP-10 was linked to favourable PFS. Conclusions: Our findings suggest the potential utility of plasma cytokine and chemokine profiles in clinical benefits of mRCC patient to the combination of Pexa-Vec and cemiplimab, thereby aiding in future personalized treatment approaches.
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Gyorffy, Balazs. "Abstract P4-07-20: Survival analysis using the entire transcriptome to pinpoint biomarkers with the highest prognostic power." Cancer Research 82, no. 4_Supplement (2022): P4–07–20—P4–07–20. http://dx.doi.org/10.1158/1538-7445.sabcs21-p4-07-20.
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Abstract Introduction. Extensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of such marker candidates compared to other genes is virtually absent. Here, we present the ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer. Methods. We searched the GEO repository to uncover transcriptomic datasets with available follow-up and clinical data. After quality control and normalization, samples entered an integrated database. Molecular subtypes were designated using gene expression data. Survival analysis was performed using Cox proportional hazards regression. False discovery rate was computed to combat multiple hypothesis testing. Kaplan-Meier plots were drawn to visualize the best performing genes. Results. The entire database includes 7,830 unique samples from 55 independent datasets. Of those with available relapse-free survival time, 3,382 samples were estrogen receptor-positive and 696 were basal. In chemotherapy treated ER positive/ERBB2 negative patients the significant prognostic biomarker genes achieved hazard rates between 1.76 and 3.33 with a p value below 5.8E-04. The significant prognostic genes in adjuvant chemotherapy treated basal breast cancer samples reached hazard rates between 1.88 and 3.61 with a p value below 7.2E-04. Finally, an online accessible platform utilizing the entire database was set up enabling the validation of future biomarker candidates. Conclusions. A reference ranking for all genes in two chemotherapy treated breast cancer cohorts is presented. The results help to neglect those with unlikely clinical significance and to focus future research on the most promising candidates. Citation Format: Balazs Gyorffy. Survival analysis using the entire transcriptome to pinpoint biomarkers with the highest prognostic power [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P4-07-20.
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Guo, Wenge, Li He, and Sanat K. Sarkar. "Further results on controlling the false discovery proportion." Annals of Statistics 42, no. 3 (2014): 1070–101. http://dx.doi.org/10.1214/14-aos1214.
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Pawitan, Y., S. Calza, and A. Ploner. "Estimation of false discovery proportion under general dependence." Bioinformatics 22, no. 24 (2006): 3025–31. http://dx.doi.org/10.1093/bioinformatics/btl527.
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Fan, Jianqing, Xu Han, and Weijie Gu. "Estimating False Discovery Proportion Under Arbitrary Covariance Dependence." Journal of the American Statistical Association 107, no. 499 (2012): 1019–35. http://dx.doi.org/10.1080/01621459.2012.720478.
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Ditzhaus, Marc, and Arnold Janssen. "Variability and stability of the false discovery proportion." Electronic Journal of Statistics 13, no. 1 (2019): 882–910. http://dx.doi.org/10.1214/19-ejs1544.
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Javanmard, Adel, and Andrea Montanari. "Online rules for control of false discovery rate and false discovery exceedance." Annals of Statistics 46, no. 2 (2018): 526–54. http://dx.doi.org/10.1214/17-aos1559.
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Hemerik, J., A. Solari, and J. J. Goeman. "Permutation-based simultaneous confidence bounds for the false discovery proportion." Biometrika 106, no. 3 (2019): 635–49. http://dx.doi.org/10.1093/biomet/asz021.
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SummaryWhen multiple hypotheses are tested, interest is often in ensuring that the proportion of false discoveries is small with high confidence. In this paper, confidence upper bounds for the false discovery proportion are constructed, which are simultaneous over all rejection cut-offs. In particular, this allows the user to select a set of hypotheses post hoc such that the false discovery proportion lies below some constant with high confidence. Our method uses permutations to account for the dependence structure in the data. So far only Meinshausen (2006) has developed an exact, permutation-based and computationally feasible method for obtaining simultaneous false discovery proportion bounds. We propose an exact method which uniformly improves that procedure. Further, we provide a generalization of the method that lets the user select the shape of the simultaneous confidence bounds; this gives the user more freedom in determining the power properties of the method. Interestingly, several existing permutation methods, such as significance analysis of microarrays and the maxT method of Westfall & Young (1993), are obtained as special cases.
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Hu, James X., Hongyu Zhao, and Harrison H. Zhou. "False Discovery Rate Control With Groups." Journal of the American Statistical Association 105, no. 491 (2010): 1215–27. http://dx.doi.org/10.1198/jasa.2010.tm09329.
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Perone Pacifico, M., C. Genovese, I. Verdinelli, and L. Wasserman. "False Discovery Control for Random Fields." Journal of the American Statistical Association 99, no. 468 (2004): 1002–14. http://dx.doi.org/10.1198/0162145000001655.
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Holte, Sarah E., Eva K. Lee, and Yajun Mei. "Symmetric directional false discovery rate control." Statistical Methodology 33 (December 2016): 71–82. http://dx.doi.org/10.1016/j.stamet.2016.08.002.
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Wu, Wei Biao. "On false discovery control under dependence." Annals of Statistics 36, no. 1 (2008): 364–80. http://dx.doi.org/10.1214/009053607000000730.
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