Dataset Information

Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation.

ABSTRACT: Background/objectives: Genetic contributors to obesity are frequently studied in murine models. However, the sample sizes of these studies are often small, and the data may violate assumptions of common statistical tests, such as normality of distributions. We examined whether, in these cases, type I error rates and power are affected by the choice of statistical test.

Subjects/methods: We conducted "plasmode"-based simulation using empirical data on body mass (weight) from murine genetic models of obesity. For the type I error simulation, the weight distributions were adjusted to ensure no difference in means between control and mutant groups. For the power simulation, the distributions of the mutant groups were shifted to ensure specific effect sizes. Three to twenty mice were resampled from the empirical distributions to create a plasmode. We then computed type I error rates and power for five common tests on the plasmodes: Student's t test, Welch's t test, Wilcoxon rank sum test (aka, Mann-Whitney U test), permutation test, and bootstrap test.

Results: We observed type I error inflation for all tests, except the bootstrap test, with small samples (?5). Type I error inflation decreased as sample size increased (?8) but remained. The Wilcoxon test should be avoided because of heterogeneity of distributions. For power, a departure from the reference was observed with small samples for all tests. Compared with the other tests, the bootstrap test had less power with small samples.

Conclusions: Overall, the bootstrap test is recommended for small samples to avoid type I error inflation, but this benefit comes at the cost of lower power. When sample size is large enough, Welch's t test is recommended because of high power with minimal type I error inflation.

SUBMITTER: Ejima K

PROVIDER: S-EPMC7261642 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation.

Ejima Keisuke K Brown Andrew W AW Smith Daniel L DL Beyaztas Ufuk U Allison David B DB

International journal of obesity (2005) 20200225 6

<h4>Background/objectives</h4>Genetic contributors to obesity are frequently studied in murine models. However, the sample sizes of these studies are often small, and the data may violate assumptions of common statistical tests, such as normality of distributions. We examined whether, in these cases, type I error rates and power are affected by the choice of statistical test.<h4>Subjects/methods</h4>We conducted "plasmode"-based simulation using empirical data on body mass (weight) from murine g ...[more]

PMID: 32099106

Similar Datasets

Project description:The mouse is a useful preclinical species for evaluating disease etiology due to the availability of a wide variety of genetically modified strains and the ability to perform disease-modifying manipulations. In order to establish an atrial filtration (AF) model in our laboratory, we profiled several commonly used murine AF models. We initially evaluated a pharmacological model of acute carbachol (CCh) treatment plus atrial burst pacing in C57BL/6 mice. In an effort to observe micro-reentrant circuits indicative of authentic AF, we employed optical mapping imaging in isolated mouse hearts. While CCh reduced atrial refractoriness and increased atrial tachyarrhythmia vulnerability, the left atrial (LA) excitation patterns were rather regular without reentrant circuits or wavelets. Therefore, the atrial tachyarrhythmia resembled high frequency atrial flutter, not typical AF per se. We next examined both a chronic angiotensin II (Ang II) infusion model and the surgical model of transverse aortic constriction (TAC), which have both been reported to induce atrial and ventricular structural changes that serve as a substrates for micro-reentrant AF. Although we observed some extent of atrial remodeling such as fibrosis or enlarged LA diameter, burst pacing-induced atrial tachyarrhythmia vulnerability did not differ from control mice in either model. This again suggested that an AF-like pathophysiology is difficult to demonstrate in the mouse. To continue searching for a valid murine AF model, we studied mice with a cardiac-specific deficiency (KO) in liver kinase B1 (Cardiac-LKB1), which has been reported to exhibit spontaneous AF. Indeed, the electrocardiograms (ECG) of conscious Cardiac-LKB1 KO mice exhibited no P waves and had irregular RR intervals, which are characteristics of AF. Histological evaluation of Cardiac-LKB1 KO mice revealed dilated and fibrotic atria, again consistent with AF. However, atrial electrograms and optical mapping revealed that electrical activity was limited to the sino-atrial node area with no electrical conduction into the atrial myocardium beyond. Thus, Cardiac-LKB1 KO mice have severe atrial myopathy or atrial standstill, but not AF. In summary, the atrial tachyarrhythmias we observed in the four murine models were distinct from typical human AF, which often exhibits micro- or macro-reentrant atrial circuits. Our results suggest that the four murine AF models we examined may not reflect human AF well, and raise a cautionary note for use of those murine models to study AF.

Project description:BackgroundAnopheles gambiae M and S molecular forms, the major malaria vectors in the Afro-tropical region, are ongoing a process of ecological diversification and adaptive lineage splitting, which is affecting malaria transmission and vector control strategies in West Africa. These two incipient species are defined on the basis of single nucleotide differences in the IGS and ITS regions of multicopy rDNA located on the X-chromosome. A number of PCR and PCR-RFLP approaches based on form-specific SNPs in the IGS region are used for M and S identification. Moreover, a PCR-method to detect the M-specific insertion of a short interspersed transposable element (SINE200) has recently been introduced as an alternative identification approach. However, a large-scale comparative analysis of four widely used PCR or PCR-RFLP genotyping methods for M and S identification was never carried out to evaluate whether they could be used interchangeably, as commonly assumed.ResultsThe genotyping of more than 400 A. gambiae specimens from nine African countries, and the sequencing of the IGS-amplicon of 115 of them, highlighted discrepancies among results obtained by the different approaches due to different kinds of biases, which may result in an overestimation of MS putative hybrids, as follows: i) incorrect match of M and S specific primers used in the allele specific-PCR approach; ii) presence of polymorphisms in the recognition sequence of restriction enzymes used in the PCR-RFLP approaches; iii) incomplete cleavage during the restriction reactions; iv) presence of different copy numbers of M and S-specific IGS-arrays in single individuals in areas of secondary contact between the two forms.ConclusionsThe results reveal that the PCR and PCR-RFLP approaches most commonly utilized to identify A. gambiae M and S forms are not fully interchangeable as usually assumed, and highlight limits of the actual definition of the two molecular forms, which might not fully correspond to the two A. gambiae incipient species in their entire geographical range. These limits are discussed and operational suggestions on the choice of the most convenient method for large-scale M- and S-form identification are provided, also taking into consideration technical aspects related to the epidemiological characteristics of different study areas.

Dataset Information

Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation.

Publications

Murine genetic models of obesity: type I error rates and the power of commonly used analyses as assessed by plasmode-based simulation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets