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Journal articles on the topic 'Variance stabilizing transformation'

Author: Grafiati

Published: 20 April 2024

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1

Guerrero, Victor M., and Rafael Perera. "Variance Stabilizing Power Transformation for Time Series." Journal of Modern Applied Statistical Methods 3, no. 2 (November 1, 2004): 357–69. http://dx.doi.org/10.22237/jmasm/1099267740.

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2

Woodruff, David L., and Gerrit Slevogt. "Variance stabilizing transformation of wind forecast errors." Wind Energy 19, no. 10 (December 16, 2015): 1845–52. http://dx.doi.org/10.1002/we.1954.

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3

Lin, Simon M., Pan Du, Wolfgang Huber, and Warren A. Kibbe. "Model-based variance-stabilizing transformation for Illumina microarray data." Nucleic Acids Research 36, no. 2 (January 4, 2008): e11-e11. http://dx.doi.org/10.1093/nar/gkm1075.

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4

Durbin, B. P., J. S. Hardin, D. M. Hawkins, and D. M. Rocke. "A variance-stabilizing transformation for gene-expression microarray data." Bioinformatics 18, Suppl 1 (July 1, 2002): S105—S110. http://dx.doi.org/10.1093/bioinformatics/18.suppl_1.s105.

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5

Kwan, Andy C. C., and Ah-Boon Sim. "Portmanteau tests of randomness and Jenkins' variance-stabilizing transformation." Economics Letters 50, no. 1 (January 1996): 41–49. http://dx.doi.org/10.1016/0165-1765(95)00710-5.

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6

Sarno, Emma. "A variance stabilizing transformation for the Gini concentration ratio." Journal of the Italian Statistical Society 7, no. 1 (April 1998): 77–91. http://dx.doi.org/10.1007/bf03178922.

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7

Routray, Sidheswar, Arun Kumar Ray, and Chandrabhanu Mishra. "MRI Denoising using Sparse Based Curvelet Transform with Variance Stabilizing Transformation Framework." Indonesian Journal of Electrical Engineering and Computer Science 7, no. 1 (July 1, 2017): 116. http://dx.doi.org/10.11591/ijeecs.v7.i1.pp116-122.

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We develop an efficient MRI denoising algorithm based on sparse representation and curvelet transform with variance stabilizing transformation framework. By using sparse representation, a MR image is decomposed into a sparsest coefficients matrix with more no of zeros. Curvelet transform is directional in nature and it preserves the important edge and texture details of MR images. In order to get sparsity and texture preservation, we post process the denoising result of sparse based method through curvelet transform. To use our proposed sparse based curvelet transform denoising method to remove rician noise in MR images, we use forward and inverse variance-stabilizing transformations. Experimental results reveal the efficacy of our approach to rician noise removal while well preserving the image details. Our proposed method shows improved performance over the existing denoising methods in terms of PSNR and SSIM for T1, T2 weighted MR images.

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8

Dunning, Mark J., Matthew E. Ritchie, Nuno L. Barbosa-Morais, Simon Tavaré, and Andy G. Lynch. "Spike-in validation of an Illumina-specific variance-stabilizing transformation." BMC Research Notes 1, no. 1 (2008): 18. http://dx.doi.org/10.1186/1756-0500-1-18.

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9

Zhang, Minghui, Fengqin Zhang, Qiegen Liu, and Shanshan Wang. "VST-Net: Variance-stabilizing transformation inspired network for Poisson denoising." Journal of Visual Communication and Image Representation 62 (July 2019): 12–22. http://dx.doi.org/10.1016/j.jvcir.2019.04.011.

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10

Fujisawa, Hironori. "Variance stabilizing transformation and studentization for estimator of correlation coefficient." Statistics & Probability Letters 47, no. 3 (April 2000): 213–17. http://dx.doi.org/10.1016/s0167-7152(99)00158-3.

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11

Purohit, Parul V., David M. Rocke, Mark R. Viant, and David L. Woodruff. "Discrimination Models Using Variance-Stabilizing Transformation of Metabolomic NMR Data." OMICS: A Journal of Integrative Biology 8, no. 2 (July 2004): 118–30. http://dx.doi.org/10.1089/1536231041388348.

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12

Zhang, Wei, Baolin Mao, Xiaozhao Chen, Luyang Wang, Shengyu Fan, Yueyang Teng, and Yan Kang. "Low-Dose Computed Tomography Image Denoising with Variance-Stabilizing Transformation and Noise Variance Estimation." Journal of Medical Imaging and Health Informatics 6, no. 5 (September 1, 2016): 1345–59. http://dx.doi.org/10.1166/jmihi.2016.1924.

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13

Uniejewski, Bartosz, and Rafał Weron. "Efficient Forecasting of Electricity Spot Prices with Expert and LASSO Models." Energies 11, no. 8 (August 6, 2018): 2039. http://dx.doi.org/10.3390/en11082039.

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Recent electricity price forecasting (EPF) studies suggest that the least absolute shrinkage and selection operator (LASSO) leads to well performing models that are generally better than those obtained from other variable selection schemes. By conducting an empirical study involving datasets from two major power markets (Nord Pool and PJM Interconnection), three expert models, two multi-parameter regression (called baseline) models and four variance stabilizing transformations combined with the seasonal component approach, we discuss the optimal way of implementing the LASSO. We show that using a complex baseline model with nearly 400 explanatory variables, a well chosen variance stabilizing transformation (asinh or N-PIT), and a procedure that recalibrates the LASSO regularization parameter once or twice a day indeed leads to significant accuracy gains compared to the typically considered EPF models. Moreover, by analyzing the structures of the best LASSO-estimated models, we identify the most important explanatory variables and thus provide guidelines to structuring better performing models.

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14

Francis Harrison, Paul. "Varistran: Anscombe's variance stabilizing transformation for RNA-seq gene expression data." Journal of Open Source Software 2, no. 16 (August 27, 2017): 257. http://dx.doi.org/10.21105/joss.00257.

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15

INOUE, MASATO, SHIN-ICHI NISHIMURA, GEN HORI, HIROYUKI NAKAHARA, MICHIKO SAITO, YOSHIHIRO YOSHIHARA, and SHUN-ICHI AMARI. "IMPROVED PARAMETER ESTIMATION FOR VARIANCE-STABILIZING TRANSFORMATION OF GENE-EXPRESSION MICROARRAY DATA." Journal of Bioinformatics and Computational Biology 02, no. 04 (December 2004): 669–79. http://dx.doi.org/10.1142/s0219720004000806.

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A gene-expression microarray datum is modeled as an exponential expression signal (log-normal distribution) and additive noise. Variance-stabilizing transformation based on this model is useful for improving the uniformity of variance, which is often assumed for conventional statistical analysis methods. However, the existing method of estimating transformation parameters may not be perfect because of poor management of outliers. By employing an information normalization technique, we have developed an improved parameter estimation method, which enables statistically more straightforward outlier exclusion and works well even in the case of small sample size. Validation of this method with experimental data has suggested that it is superior to the conventional method.

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16

Song, Kai-Sheng. "Asymptotic Relative Efficiency and Exact Variance Stabilizing Transformation for the Generalized Gaussian Distribution." IEEE Transactions on Information Theory 59, no. 7 (July 2013): 4389–96. http://dx.doi.org/10.1109/tit.2013.2249182.

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17

McLean, Angus M., Donald A. Ruggirello, Christopher Banfield, Mario A. Gonzalez, and Meir Bialer. "Application of a Variance-Stabilizing Transformation Approach to Linear Regression of Calibration Lines." Journal of Pharmaceutical Sciences 79, no. 11 (November 1990): 1005–8. http://dx.doi.org/10.1002/jps.2600791112.

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18

France, R. L. "Aggregation in Littoral Amphipod Populations: Transformation Controversies Revisited." Canadian Journal of Fisheries and Aquatic Sciences 44, no. 8 (August 1, 1987): 1510–15. http://dx.doi.org/10.1139/f87-182.

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Spatial variability in amphipod (Hyalella azteca) density was examined in 17 Canadian Shield Lakes in south-central Ontario. Aggregation was measured by the exponent of the power relationship between density and variance. The average b index was 1.45, although this value varied depending on lake and habitat type. Whereas this should indicate the use of a fourth-root transformation, neither this nor the logarithmic transformation was as effective as the square-root in stabilizing variance. A literature review suggests that if a universal transformation is sought for benthos data, it should not be the commonly used log transformation. The observation that the square-root transformation seemed to work better on average than the fourth-root transformation, even in the region suggested by theory for the latter, suggests that complications may arise in the uncritical use of Taylor's Power Law.

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19

Gerke, Oke, and Sören Möller. "Modeling Bland–Altman Limits of Agreement with Fractional Polynomials—An Example with the Agatston Score for Coronary Calcification." Axioms 12, no. 9 (September 15, 2023): 884. http://dx.doi.org/10.3390/axioms12090884.

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Bland–Altman limits of agreement are very popular in method comparison studies on quantitative outcomes. However, a straightforward application of Bland–Altman analysis requires roughly normally distributed differences, a constant bias, and variance homogeneity across the measurement range. If one or more assumptions are violated, a variance-stabilizing transformation (e.g., natural logarithm, square root) may be sufficient before Bland–Altman analysis can be performed. Sometimes, fractional polynomial regression has been used when the choice of variance-stabilizing transformation was unclear and increasing variability in the differences was observed with increasing mean values. In this case, regressing the absolute differences on a function of the average and applying fractional polynomial regression to this end were previously proposed. This review revisits a previous inter-rater agreement analysis on the Agatston score for coronary calcification. We show the inappropriateness of a straightforward Bland–Altman analysis and briefly describe the nonparametric limits of agreement of the original investigation. We demonstrate the application of fractional polynomials, use the Stata packages fp and fp_select, and discuss the use of degree-2 (the default setting) and degree-3 fractional polynomials. Finally, we discuss conditions for evaluating the appropriateness of nonstandard limits of agreement.

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20

Adubisi, Obinna. "Predictive Model with Square-Root Variance Stabilizing Transformation for Nigeria Crude Oil Export to America." Science Journal of Applied Mathematics and Statistics 5, no. 5 (2017): 174. http://dx.doi.org/10.11648/j.sjams.20170505.12.

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21

Ma, Xiaodong, Kâmil Uğurbil, and Xiaoping Wu. "Denoise magnitude diffusion magnetic resonance images via variance-stabilizing transformation and optimal singular-value manipulation." NeuroImage 215 (July 2020): 116852. http://dx.doi.org/10.1016/j.neuroimage.2020.116852.

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22

Makitalo, Markku, and Alessandro Foi. "A Closed-Form Approximation of the Exact Unbiased Inverse of the Anscombe Variance-Stabilizing Transformation." IEEE Transactions on Image Processing 20, no. 9 (September 2011): 2697–98. http://dx.doi.org/10.1109/tip.2011.2121085.

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23

Sid Ahmed, Soumia, Zoubeida Messali, Florent Poyer, Livia Lumbroso-Le Rouic, Laurence Desjardins, Nathalie Cassoux, Carole D. Thomas, Sergio Marco, and Stéphanie Lemaitre. "Iterative Variance Stabilizing Transformation Denoising of Spectral Domain Optical Coherence Tomography Images Applied to Retinoblastoma." Ophthalmic Research 59, no. 3 (2018): 164–69. http://dx.doi.org/10.1159/000486283.

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24

Reddon, John R. "Fisher’s Tanh−1 Transformation of the Correlation Coefficient and a Test for Complete Independence in a Multivariate Normal Population." Journal of Educational Statistics 12, no. 3 (September 1987): 294–300. http://dx.doi.org/10.3102/10769986012003294.

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Computer sampling from a multivariate normal spherical population was used to evaluate Type I error rates for a test of P = I based on Fisher’s tanh−1 variance stabilizing transformation of the correlation coefficient. The range of variates considered was 5 to 25 and Type I error rates were estimated for several sample sizes with 2,500 independent replications. Except for small samples the test was well behaved. After the test converges to an acceptable Type I error rate it is preferable to Box’s test of P = I.

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25

Wagner, G. P. "Multivariate mutation-selection balance with constrained pleiotropic effects." Genetics 122, no. 1 (May 1, 1989): 223–34. http://dx.doi.org/10.1093/genetics/122.1.223.

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Abstract A multivariate quantitative genetic model is analyzed that is based on the assumption that the genetic variation at a locus j primarily influences an underlying physiological variable yj, while influence on the genotypic values is determined by a kind of "developmental function" which is not changed by mutations at this locus. Assuming additivity among loci the developmental function becomes a linear transformation of the underlying variables y onto the genotypic values x, x = By. In this way the pleiotropic effects become constrained by the structure of the B-matrix. The equilibrium variance under mutation-stabilizing selection balance in infinite and finite populations is derived by using the house of cards approximation. The results are compared to the predictions given by M. Turelli in 1985 for pleiotropic two-character models. It is shown that the B-matrix model gives the same results as Turelli's five-allele model, suggesting that the crucial factor determining the equilibrium variance in multivariate models with pleiotropy is the assumption about constraints on the pleiotropic effects, and not the number of alleles as proposed by Turelli. Finally it is shown that under Gaussian stabilizing selection the structure of the B-matrix has effectively no influence on the mean equilibrium fitness of an infinite population. Hence the B-matrix and consequently to some extent also the structure of the genetic correlation matrix is an almost neutral character. The consequences for the evolution of genetic covariance matrices are discussed.

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26

Janczura, Joanna, and Andrzej Puć. "ARX-GARCH Probabilistic Price Forecasts for Diversification of Trade in Electricity Markets—Variance Stabilizing Transformation and Financial Risk-Minimizing Portfolio Allocation." Energies 16, no. 2 (January 10, 2023): 807. http://dx.doi.org/10.3390/en16020807.

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In this paper, we propose dynamic, short-term, financial risk management strategies for small electricity producers and buyers that trade in the wholesale electricity markets. Since electricity is mostly nonstorable, financial risk coming from extremely volatile electricity prices cannot be reduced by using standard finance-based approaches. Instead, a short-term operational planing and a proper trade diversification might be used. In this paper, we analyze the price risk in terms of the Markowitz mean–variance portfolio theory. Hence, it is crucial to forecast properly the variance of electricity prices. To this end, we jointly model day-ahead and intraday or balancing prices from Germany and Poland using ARX-GARCH type models. We show that using heteroscedastic volatility significantly improves probabilistic price forecasts according to the pinball score, especially if variance stabilizing transformation is applied prior to a model estimation. The price forecasts are then used for construction of dynamic diversification strategies that are based on volatility-type risk measures. We consider different objectives as well as a buyer’s and a seller’s perspective. The proposed strategies are applied for the diversification of trade among different markets in Germany and Poland. We show that the objective of the strategy can be achieved using the proposed approach, but the risk minimization is usually related to lower profits. We find that risk minimization is especially important for a seller in both markets, while for a buyer a profit maximization objective leads to a more optimal risk–return trade-off.

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27

Bosse, Nikos I., Sam Abbott, Anne Cori, Edwin van Leeuwen, Johannes Bracher, and Sebastian Funk. "Scoring epidemiological forecasts on transformed scales." PLOS Computational Biology 19, no. 8 (August 29, 2023): e1011393. http://dx.doi.org/10.1371/journal.pcbi.1011393.

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Forecast evaluation is essential for the development of predictive epidemic models and can inform their use for public health decision-making. Common scores to evaluate epidemiological forecasts are the Continuous Ranked Probability Score (CRPS) and the Weighted Interval Score (WIS), which can be seen as measures of the absolute distance between the forecast distribution and the observation. However, applying these scores directly to predicted and observed incidence counts may not be the most appropriate due to the exponential nature of epidemic processes and the varying magnitudes of observed values across space and time. In this paper, we argue that transforming counts before applying scores such as the CRPS or WIS can effectively mitigate these difficulties and yield epidemiologically meaningful and easily interpretable results. Using the CRPS on log-transformed values as an example, we list three attractive properties: Firstly, it can be interpreted as a probabilistic version of a relative error. Secondly, it reflects how well models predicted the time-varying epidemic growth rate. And lastly, using arguments on variance-stabilizing transformations, it can be shown that under the assumption of a quadratic mean-variance relationship, the logarithmic transformation leads to expected CRPS values which are independent of the order of magnitude of the predicted quantity. Applying a transformation of log(x + 1) to data and forecasts from the European COVID-19 Forecast Hub, we find that it changes model rankings regardless of stratification by forecast date, location or target types. Situations in which models missed the beginning of upward swings are more strongly emphasised while failing to predict a downturn following a peak is less severely penalised when scoring transformed forecasts as opposed to untransformed ones. We conclude that appropriate transformations, of which the natural logarithm is only one particularly attractive option, should be considered when assessing the performance of different models in the context of infectious disease incidence.

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28

Davies, Georgina, and Noel Cressie. "Analysis of variability of tropical Pacific sea surface temperatures." Advances in Statistical Climatology, Meteorology and Oceanography 2, no. 2 (November 14, 2016): 155–69. http://dx.doi.org/10.5194/ascmo-2-155-2016.

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Abstract. Sea surface temperature (SST) in the Pacific Ocean is a key component of many global climate models and the El Niño–Southern Oscillation (ENSO) phenomenon. We shall analyse SST for the period November 1981–December 2014. To study the temporal variability of the ENSO phenomenon, we have selected a subregion of the tropical Pacific Ocean, namely the Niño 3.4 region, as it is thought to be the area where SST anomalies indicate most clearly ENSO's influence on the global atmosphere. SST anomalies, obtained by subtracting the appropriate monthly averages from the data, are the focus of the majority of previous analyses of the Pacific and other oceans' SSTs. Preliminary data analysis showed that not only Niño 3.4 spatial means but also Niño 3.4 spatial variances varied with month of the year. In this article, we conduct an analysis of the raw SST data and introduce diagnostic plots (here, plots of variability vs. central tendency). These plots show strong negative dependence between the spatial standard deviation and the spatial mean. Outliers are present, so we consider robust regression to obtain intercept and slope estimates for the 12 individual months and for all-months-combined. Based on this mean–standard deviation relationship, we define a variance-stabilizing transformation. On the transformed scale, we describe the Niño 3.4 SST time series with a statistical model that is linear, heteroskedastic, and dynamical.

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29

Fosdick, Bailey K., and Michael D. Perlman. "Variance-stabilizing and Confidence-stabilizing Transformations for the Normal Correlation Coefficient with Known Variances." Communications in Statistics - Simulation and Computation 45, no. 6 (June 2, 2016): 1918–35. http://dx.doi.org/10.1080/03610918.2014.882948.

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30

Xiaojun, Feng. "Regulating labour dispatch in China: A cat-and-mouse game." China Information 33, no. 1 (August 26, 2018): 88–109. http://dx.doi.org/10.1177/0920203x18791398.

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This article suggests cautious optimism toward the prevailing Polanyian countermovement discourse by providing a timely and comprehensive examination of the enforcement of the labour dispatch regulation in China. Since the enactment of the regulation, some enterprises have narrowed the remuneration gap between agency workers and formal employees, while others have retained a large gap in overtime pay, bonuses, and welfare benefits between these two groups of workers. The regulation has reduced the number of agency workers, but has invoked the abuse of the more precarious ‘outsourced’ workers as well. The regulation has had little effect on limiting the use of agency labour to temporary, auxiliary, or substitute positions, raising the requirements of engaging in the labour dispatch business, or stabilizing the employment of agency workers. This article contributes to the extant literature on regulatory enforcement by examining the effects of non-standard employment regulation, highlighting the variance of labour law compliance among enterprises with different types of ownership, and demonstrating how China’s ongoing transformation from a planned to a market economy since the 1980s and from high growth to a new normal since 2010 has fundamentally constrained the full implementation of its labour protection regulation.

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31

Kumar, K. Sampath, and C. Arun C. Arun. "Poisson Noise Removal From Flourescence Images Using Optimized Variance-Stabilizing Transformations And Standard Gaussian Denoising Strategies." Indian Journal of Applied Research 1, no. 3 (October 1, 2011): 79–82. http://dx.doi.org/10.15373/2249555x/dec2011/28.

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32

Lahiri, S. N. "Variance stabilizing transformations, studentization and the bootstrap." Journal of Statistical Planning and Inference 61, no. 1 (May 1997): 105–23. http://dx.doi.org/10.1016/s0378-3758(97)89715-7.

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33

Durbin, B. P., and D. M. Rocke. "Variance-stabilizing transformations for two-color microarrays." Bioinformatics 20, no. 5 (January 22, 2004): 660–67. http://dx.doi.org/10.1093/bioinformatics/btg464.

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34

Nazarzadeh, Milad, Zeinab Bidel, Alireza Mosavi Jarahi, Keihan Esmaeelpour, Walieh Menati, Ali Asghar Shakeri, Rostam Menati, Sattar Kikhavani, and Kourosh Saki. "Prevalence of Cannabis Lifetime Use in Iranian High School and College Students." American Journal of Men's Health 9, no. 5 (August 20, 2014): 397–409. http://dx.doi.org/10.1177/1557988314546667.

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Cannabis is the most widely used substance in the world. This study aimed to estimate the prevalence of cannabis lifetime use (CLU) in high school and college students of Iran and also to determine factors related to changes in prevalence. A systematic review of literature on cannabis use in Iran was conducted according to MOOSE guideline. Domestic scientific databases, PubMed/Medline, ISI Web of Knowledge, and Google Scholar, relevant reference lists, and relevant journals were searched up to April, 2014. Prevalences were calculated using the variance stabilizing double arcsine transformation and confidence intervals (CIs) estimated using the Wilson method. Heterogeneity was assessed by Cochran’s Q statistic and I2 index and causes of heterogeneity were evaluated using meta-regression model. In electronic database search, 4,000 citations were retrieved, producing a total of 33 studies. CLU was reported with a random effects pooled prevalence of 4.0% (95% CI = 3.0% to 5.0%). In subgroups of high school and college students, prevalences were 5.0% (95% CI = 3.0% to −7.0%) and 2.0% (95% CI = 2.0% to −3.0%), respectively. Meta-regression model indicated that prevalence is higher in college students (β = 0.089, p < .001), male gender (β = 0.017, p < .001), and is lower in studies with sampling versus census studies (β = −0.096, p < .001). This study reported that prevalence of CLU in Iranian students are lower than industrialized countries. In addition, gender, level of education, and methods of sampling are highly associated with changes in the prevalence of CLU across provinces.

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35

Uniejewski, Bartosz, Rafal Weron, and Florian Ziel. "Variance Stabilizing Transformations for Electricity Spot Price Forecasting." IEEE Transactions on Power Systems 33, no. 2 (March 2018): 2219–29. http://dx.doi.org/10.1109/tpwrs.2017.2734563.

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36

Konishi, Sadanori. "Normalizing and variance stabilizing transformations for intraclass correlations." Annals of the Institute of Statistical Mathematics 37, no. 1 (December 1985): 87–94. http://dx.doi.org/10.1007/bf02481082.

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37

Celikyurt, Ipek Komsuoglu, Guner Ulak, Oguz Mutlu, Furuzan Yildiz Akar, Faruk Erden, and Sezer Sener Komsuoglu. "Lamotrigine effects sensorimotor gating in WAG/Rij rats." Journal of Neurosciences in Rural Practice 03, no. 02 (May 2012): 126–30. http://dx.doi.org/10.4103/0976-3147.98207.

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ABSTRACTIntroduction: Prepulse inhibition (PPI) is a measurable form of sensorimotor gating. Disruption of PPI reflects the impairment in the neural filtering process of mental functions that are related to the transformation of an external stimuli to a response. Impairment of PPI is reported in neuropsychiatric illnesses such as schizophrenia, Huntington’s disease, Parkinson’s diseases, Tourette syndrome, obsessive compulsive disorder, and temporal lobe epilepsy with psychosis. Absence epilepsy is the most common type of primary generalized epilepsy. Lamotrigine is an antiepileptic drug that is preferred in absence epilepsy and acts by stabilizing the voltage-gated sodium channels. Aim: In this study, we have compared WAG-Rij rats (genetically absence epileptic rats) with Wistar rats, in order to clarify if there is a deficient sensorimotor gating in absence epilepsy, and have examined the effects of lamotrigine (15, 30 mg/kg, i.p.) on this phenomenon. Materials and Methods: Depletion in PPI percent value is accepted as a disruption in sensory-motor filtration function. The difference between the Wistar and WAG/Rij rats has been evaluated with the student t test and the effects of lamotrigine on the PPI percent have been evaluated by the analysis of variance (ANOVA) post-hoc Dunnett’s test. Results: The PPI percent was low in the WAG/Rij rats compared to the controls (P<0.0001, t:9,612). Although the PPI percent value of the control rats was not influenced by lamotrigine, the PPI percent value of the WAG/Rij rats was raised by lamotrigine treatment (P<0.0001, F:861,24). Conclusions: As a result of our study, PPI was disrupted in the WAG/Rij rats and this disruption could be reversed by an antiepileptic lamotrigine.

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38

Rothe, Hendrik. "Improved accuracy in laser triangulation by variance-stabilizing transformations." Optical Engineering 31, no. 7 (1992): 1538. http://dx.doi.org/10.1117/12.57691.

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39

Bar-Lev, Shaul K., and Peter Enis. "On the construction of classes of variance stabilizing transformations." Statistics & Probability Letters 10, no. 2 (July 1990): 95–100. http://dx.doi.org/10.1016/0167-7152(90)90002-o.

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40

Rocke, D. M., and B. Durbin. "Approximate variance-stabilizing transformations for gene-expression microarray data." Bioinformatics 19, no. 8 (May 22, 2003): 966–72. http://dx.doi.org/10.1093/bioinformatics/btg107.

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41

Yu, Guan. "Variance stabilizing transformations of Poisson, binomial and negative binomial distributions." Statistics & Probability Letters 79, no. 14 (July 2009): 1621–29. http://dx.doi.org/10.1016/j.spl.2009.04.010.

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42

Bar-Lev, S. K., and P. Enis. "Variance stabilizing and normalizing transformations for the compound poisson process." Metrika 39, no. 1 (December 1992): 165–75. http://dx.doi.org/10.1007/bf02613996.

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43

Zhang, Chunlei, Huan Yang, Qinglei Xu, Mingzheng Liu, Xiaohuan Chao, Jiahao Chen, Bo Zhou, and Yang Liu. "Comprehensive Genome and Transcriptome Analysis Identifies SLCO3A1 Associated with Aggressive Behavior in Pigs." Biomolecules 13, no. 9 (September 12, 2023): 1381. http://dx.doi.org/10.3390/biom13091381.

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Copy number variation (CNV) represents a significant reservoir of genetic diversity within the genome and exhibits a strong association with economically valuable traits in livestock. The manifestation of aggressive behavior in pigs has detrimental effects on production efficiency, immune competency, and meat quality. Nevertheless, the impact of CNV on the aggressive behavior of pigs remains elusive. In this investigation, we employed an integrated analysis of genome and transcriptome data to investigate the interplay between CNV, gene expression changes, and indicators of aggressive behavior in weaned pigs. Specifically, a subset of pigs comprising the most aggressive pigs (MAP, n = 12) and the least aggressive pigs (LAP, n = 11) was purposefully selected from a herd of 500 weaned pigs following a mixing procedure based on their composite aggressive score (CAS). Subsequently, we thoroughly analyzed copy number variation regions (CNVRs) across the entire genome using next-generation sequencing techniques, ultimately revealing the presence of 6869 CNVRs. Using genome-wide association study (GWAS) analysis and evaluating variance-stabilizing transformation (VST) values, we successfully identified distinct CNVRs that distinguished the MAP and LAP counterparts. Among the prioritized CNVRs, CNVR-4962 (designated as the top-ranked p-value and VST value, No. 1) was located within the Solute Carrier Organic Anion Transporter Family Member 3A1 (SLCO3A1) gene. The results of our analyses indicated a significantly higher (p < 0.05) copy number of SLCO3A1 in the MAP compared to the LAP. Furthermore, this increased copy number exhibited a positive correlation with the CAS of the pigs (p < 0.05). Furthermore, we integrated genomic data with transcriptomic data from the temporal lobe to facilitate the examination of expression quantitative trait loci (eQTL). Importantly, these observations were consistent with the mRNA expression pattern of SLCO3A1 in the temporal lobe of both MAP and LAP (p < 0.05). Consequently, our findings strongly suggest that CNVs affecting SLCO3A1 may influence gene expression through a dosage effect. These results highlight the potential of SLCO3A1 as a candidate gene associated with aggressive traits in pig breeding programs.

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44

Verrel, Julius. "Distributional properties and variance-stabilizing transformations for measures of uncontrolled manifold effects." Journal of Neuroscience Methods 191, no. 2 (August 2010): 166–70. http://dx.doi.org/10.1016/j.jneumeth.2010.06.016.

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Hayakawa, Takesi. "Normalizing and variance stabilizing transformations of multivariate statistics under an elliptical population." Annals of the Institute of Statistical Mathematics 39, no. 2 (December 1987): 299–306. http://dx.doi.org/10.1007/bf02491469.

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Prucnal, Paul R., and Evan L. Goldstein. "Exact variance-stabilizing transformations for image-signal-dependent Rayleigh and other Weibull noise sources." Applied Optics 26, no. 6 (March 15, 1987): 1038. http://dx.doi.org/10.1364/ao.26.001038.

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Chaubey, Yogendra P., Murari Singh, and Debaraj Sen. "Symmetrizing and Variance Stabilizing Transformations of Sample Coefficient of Variation from Inverse Gaussian Distribution." Sankhya B 79, no. 2 (June 23, 2017): 217–46. http://dx.doi.org/10.1007/s13571-017-0136-z.

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BAR-LEV, SHAUL K., and PETER ENIS. "On the classical choice of variance stabilizing transformations and an application for a Poisson variate." Biometrika 75, no. 4 (1988): 803–4. http://dx.doi.org/10.1093/biomet/75.4.803.

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Becker, Betsy Jane. "Small-Sample Accuracy of Approximate Distributions of Functions of Observed Probabilities From t Tests." Journal of Educational Statistics 16, no. 4 (December 1991): 345–69. http://dx.doi.org/10.3102/10769986016004345.

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The observed probability p is the social scientist’s primary tool for evaluating the outcomes of statistical hypothesis tests. Functions of p s are used in tests of “combined significance,” meta-analytic summaries based on sample probability values. This study examines the nonnull asymptotic distributions of several functions of one-tailed sample probability values (from t tests). Normal approximations were based on the asymptotic distributions of z(p), the standard normal deviate associated with the one-sided p value; of ln(p), the natural logarithm of the probability value; and of several modifications of ln(p). Two additional approximations, based on variance-stabilizing transformations of ln(p) and z(p), were derived. Approximate cumulative distribution functions (cdfs) were compared to the computed exact cdf of the p associated with the one-sample t test. Approximations to the distribution of z(p) appeared quite accurate even for very small samples, while other approximations were inaccurate unless sample sizes or effect sizes were very large. Approximations based on variance-stabilizing transformations were not much more accurate than those based on ln(p) and z(p). Generalizations of the results are discussed, and implications for use of the approximations conclude the article.

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Su, Shengchen, Sungyong You, Yanping Wang, Patrick Tamukong, Catherine S. Grasso, and Hyung L. Kim. "Abstract 4178: PAK4 inhibition improves PD1 blockade immunotherapy in prostate cancer." Cancer Research 82, no. 12_Supplement (June 15, 2022): 4178. http://dx.doi.org/10.1158/1538-7445.am2022-4178.

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Abstract Prostate cancers have low immune infiltration and do not respond to PD1 blockade immunotherapy. The objective of this study was to examine the effect of PAK4 inhibition on anti-tumor immune response in preclinical prostate cancer models. C57BL/6J mice (male, 5-8 weeks old) were injected with wild type (WT) or PAK4 knockdown (KD) syngeneic Rm1 tumor cells (2X105 cell/mouse) and treated with or without αPD1 blockade (200μg, BioXCell). Tumor growth was monitored and analyzed using ANOVA of repeated measures (n=6). In a separate experiment, 1 cm RM1 tumors were collected for RNA sequencing (RNASeq) and immunohistochemistry (IHC). RNASeq data were normalized using the variance stabilizing transformation (VST) function as implemented within the DESeq2 package. IHC images were captured with Keyence BZ-X800 and positive staining was calculated using ImageJ. CD8+ lymphocytes depletion was achieved by CD8 antibody injection (200ug, BioXCell). PAK4 inhibitors PF-3758309 (PF) and KPT-9274 (KPT) were evaluated in murine models. PAK4 KD tumors treated with αPD1 antibody (αPD1) showed a significant reduction of tumor growth when compared to growth in WT (P<.05), WT αPD1 (P<.01), and KD (p<.05). Analysis of bulk tumor RNAseq showed that the combination of PAK4 KD with αPD1 was associated with increased CD8a, IFNγ, and PD-L1 expression. IHC with αCD8 verified that PAK4 KD increased CD8+ cell infiltration in mouse tumors. Further, RNAseq showed that PAK4 KD increased the expression of cytokines, chemokines, and genes related to the IFNγ response. These results suggest that PAK4 KD primes the tumor for immune infiltration and improves αPD1 treatment response. The anti-tumor effect of PAK4 KD with αPD1 in mice was CD8-dependent and could be eliminated by CD8+ cell depletion (p<.05). We tested two different PAK4 inhibitors in mice with WT Rm1 tumors. PF is a kinase inhibitor that blocks the function of PAK4. A combination of PF and αPD1 significantly reduced tumor growth when compared to WT (P<.05), WT αPD1 (P<.01), and PF (p<.05). KPT is a dual inhibitor of PAK4 and NAMPT, which reduces the cytosolic protein concentration of PAK4. A combination of KPT and αPD1 significantly reduced tumor growth when compared to WT (P<.01) and WT αPD1 (P<.01). In conclusion, PAK4 inhibition increased immune infiltration and improved αPD1 treatment response in preclinical mouse prostate cancer models. Citation Format: Shengchen Su, Sungyong You, Yanping Wang, Patrick Tamukong, Catherine S. Grasso, Hyung L. Kim. PAK4 inhibition improves PD1 blockade immunotherapy in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 4178.

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