A new family of power transformations to improve normality or symmetry

Yeo, In‐Kwon; Johnson, Richard A.

doi:10.1093/biomet/87.4.954

Cited by 1,169 publications

(776 citation statements)

References 7 publications

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“…Qualitative data were described by frequency tables with 95% CIs and analysed using Fisher's exact test. To reduce skewness and to approximate normality, Yeo-Johnson transformation was used for the regression of the HRV variables and QTVI with age, sex, BMI and drugs potentially increasing or decreasing HRV and those without a clear effect on HRV [38]. The resulting regression line was used to define the lower and upper limits of normal for all HRV indices and QTVI at the 5th and 95th percentile of the NGT population, respectively.…”

Section: Short-term Symbolic Dynamicsmentioning

confidence: 99%

Increased prevalence of cardiac autonomic dysfunction at different degrees of glucose intolerance in the general population: the KORA S4 survey

Ziegler

Voss

Rathmann³

et al. 2015

Diabetologia

101

107

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Aims/hypothesis Cardiac autonomic nervous dysfunction (CAND) raises the risk of mortality, but the glycaemic threshold at which it develops is unclear. We aimed to determine the prevalence of, risk factors for and impact of CAND in glucose intolerance and diabetes. Methods Among 1,332 eligible participants aged 55-74 years in the population-based cross-sectional KORA S4 study, 130 had known diabetes mellitus (k-DM), and the remaining 1,202 underwent an OGTT. Heart rate variability (HRV) and QT variability were computed from supine 5 min ECGs. Results In all, 565 individuals had normal glucose tolerance (NGT), 336 had isolated impaired fasting glucose (i-IFG), 72 had isolated impaired glucose tolerance (i-IGT), 151 had combined IFG-IGT (IFG-IGT) and 78 had newly detected diabetes mellitus (n-DM). Adjusted normal HRV limits were defined in the NGT population (5th and 95th percentiles). Three HRV measures were more frequently abnormal in those with k-DM, n-DM, IFG-IGT and i-IFG than in those with NGT (p<0.05). The rates of CAND (≥2 of 4 HRV indices abnormal) were: NGT, 4.5%; i-IFG, 8.1%; i-IGT, 5.9%; IFG-IGT, 11.4%; n-DM, 11.7%; and k-DM, 17.5% (p<0.05 vs NGT, except for i-IGT). Reduced HRV was associated with cardiovascular risk factors used to construct a simple screening score for CAND. Mortality was higher in participants with reduced HRV (p<0.05 vs normal HRV). Conclusions/interpretation In the general population aged 55-74 years, the prevalence of CAND is increased not only in individuals with diabetes, but also in those with IFG-IGT and, to a lesser degree, in those with i-IFG. It is associated with mortality and modifiable cardiovascular risk factors which may be used to screen for diminished HRV in clinical practice.

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Section: Short-term Symbolic Dynamicsmentioning

confidence: 99%

Increased prevalence of cardiac autonomic dysfunction at different degrees of glucose intolerance in the general population: the KORA S4 survey

Ziegler

Voss

Rathmann³

et al. 2015

Diabetologia

101

107

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“…This is determined by computing a z-score upon Yeo-Johnson (YJ) 16 transformed data. This transformation, shown in Equation 1, ensures that the data is sufficiently normally distributed to be amenable to parametric testing.…”

Section: Methodsmentioning

confidence: 99%

Validation of predicted mRNA splicing mutations using high-throughput transcriptome data

et al. 2014

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Interpretation of variants present in complete genomes or exomes reveals numerous sequence changes, only a fraction of which are likely to be pathogenic. Mutations have been traditionally inferred from allele frequencies and inheritance patterns in such data. Variants predicted to alter mRNA splicing can be validated by manual inspection of transcriptome sequencing data, however this approach is intractable for large datasets. These abnormal mRNA splicing patterns are characterized by reads demonstrating either exon skipping, cryptic splice site use, and high levels of intron inclusion, or combinations of these properties. We present, Veridical, an in silico method for the automatic validation of DNA sequencing variants that alter mRNA splicing. Veridical performs statistically valid comparisons of the normalized read counts of abnormal RNA species in mutant versus non-mutant tissues. This leverages large numbers of control samples to corroborate the consequences of predicted splicing variants in complete genomes and exomes.

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“…In order to improve normality, we use the power transformation of Yeo-Johnson [17] in this case of the nonnegative values of the variable with empirically determined in our case coefficient 0.4 from the expression…”

Section: Study Area Data and Data Pre-processesingmentioning

confidence: 99%