Statistical power comparisons among alternative morphometric methods

This paper compares the statistical power of various tests that have been proposed to test for equality of shape in two populations. Power surfaces are computed with emphasis on the simplest case of three points in the plane (i.e., landmarks at the vertices of a triangle). Goodall's ([1991] J Roy Stat Soc Serb 53:285-339) F-test was found to have the highest power followed by T(2)-tests using Kendall tangent space coordinates. Power for T(2)-tests using Bookstein shape coordinates was good if the baseline was not the shortest side of the triangle. The Rao and Suryawanshi ([1996] Proc Natl Acad Sci 93:12132-12136 and Rao and Suryawanshi [1998] Proc Natl Acad Sci 95:4121-4125) shape variables had much lower power when triangles were not close to being equilateral. Power surfaces for the EDMA-I T statistic revealed very low power for many shape comparisons including those between very different shapes. Power surface for the EDMA-II Z statistic were also complicated and depended strongly on the choice of baseline used for size scaling. The type I error rate was also often not correct for this method. Results for more than three landmarks are also presented. The implications of the results for practical applications of morphometrics are discussed.     

Reproducibility of morphometric measurements of amyloid after various staining methods

Four histologic staining methods used for detecting amyloid (Congo red, viewed in both normal and polarized light, Sirius red, Crystal violet and Thioflavine T) were applied to heart muscle autopsy samples from 19 patients who suffered from amyloidosis. The amount of amyloid present was evaluated with morphometry (point counting) by five pathologists, and the interobserver reproducibility and variation of point counting in these staining methods were analyzed. The Sirius red method showed the least variation and was the most suitable stain for demonstrating amyloid with respect to reproducibility. Thioflavine T showed the greatest variation and was the least suitable stain with respect to reproducibility. The range of variation was considerable in all staining methods. The results show that stains differ in their specificity and sensitivity in staining amyloid, observers differ in their interpretation of staining results and certain stains result in more uniform interpretations than do others.     

Lipoprotein (a) measurements for clinical application

The high degree of size heterogeneity of apo(a), the distinct protein component of lipoprotein (a) [Lp(a)], renders the development and selection of specific antibodies directed to apo(a) more difficult and poses significant challenges to the development of immunoassays to measure its concentration in plasma or serum samples. Apo(a) is extremely variable in size not only between but also within individuals because of the presence of two different, genetically determined apo(a) isoform sizes. Therefore, the antigenic determinants per particle available to interact with the antibodies will vary in the samples and the calibrators, thus contributing to apo(a) size-dependent inaccuracy of different methods. The lack of rigorous validation of the immunoassays and common means of expressing Lp(a) concentrations hinder the harmonization of results obtained by different studies and contribute to the lack of common cut points for identification of individuals at risk for coronary artery disease or for interventions aimed at reducing Lp(a) levels. The aim of our review is to present and critically evaluate the issues surrounding the measurements of Lp(a), their impact on the clinical interpretation of the data, and the obstacles we need to overcome to achieve the standardization of Lp(a) measurements.     

Statistical models for analyzing repeated quality measurements of horticultural products. Model evaluations and practical example

In the field of postharvest quality assessment of horticultural products, research on the development of non-destructive quality sensors, replacing destructive and often time consuming sensors, has spurred in the last decennium offering the possibility of taking repeated quality measures on the same product. Repeated measures analysis is gaining importance during recent years and several software packages offer a broad class of routines. A dataset dealing with the postharvest quality evolution of different tomato cultivars serves as practical example for the comparison and discussion of four different statistical model types. Starting from an analysis at each time point and an ordinary least squares regression model as standard and widely used methods, this contribution aims at comparing these two methods to a repeated measures analysis and a longitudinal mixed model. It is shown that the flexibility of such a mixed model, both towards the repeated measures design of the experiments as towards the large product variability inherent to these horticultural products, is an important advantage over classical techniques. This research shows that different conclusions could be drawn depending on which technique is used due to the basic assumptions of each model and which are not always fulfilled. The results further demonstrate the flexibility of the mixed model concept. Using a mixed model for repeated measures, the different sources of variability, being inter-tomato variability, intra-tomato variability and measurement error were characterized being of great benefit to the researcher.     

Effective methods for practical application of gene expression analysis in field-grown rice roots

Background and aims

Gene expression analysis under field conditions improves our understanding of crop responses to fluctuating environmental conditions. We evaluated RNA extraction methods and reference genes for a quantitative real-time PCR study of rice roots grown under field conditions.

Methods

Roots were collected from paddy (Andosol) at different growth stages, from tillering to ripening. RNA was extracted by three methods using commercially available RNA-extraction kits, and RNA yield and quality were compared.

Results

Our RNA extraction method enabled us to obtain adequate concentration and yield of RNA from the roots during a broad period of growth. Adequate RNA concentration was successfully extracted from the field-grown rice roots using large quantities of tissue samples and by purifying the samples prior to the extraction. Among the seven candidate reference genes, TATA-binding protein coding gene (TBP2) was observed to be highly stable across all the root samples and growth stages, in real-time PCR assays. Root gene expression analysis of water channel- and nitrogen uptake-related proteins clearly indicated dynamic changes (with respect to diurnal and growth stages) in their expression levels and their associations with meteorological factors. Some aquaporin genes such as OsPIP1;3, OsPIP2;4, and OsPIP2;5, showed clear diurnal changes. Among them, the expression pattern of OsPIP2;5 paralleled the potential evaporation (Ep) and leaf stomatal conductance on a sunny day. The gene expression analysis clearly showed diverse expression patterns; the gene expression levels of many aquaporins decreased after panicle formation stage, whereas the abundance of some genes such as OsNIP2;1 and OsAMT1;3 increased at the later growth stage.

Conclusion

Our method will be useful for evaluating the variations of gene expression in the roots of field-grown rice under fluctuating environmental condition.

     

Statistical variation of selected clinical pathological and biochemical measurements in rodents

The variability in clinical pathological and biochemical measurements among replicates is often greater than the effects under study. To minimize the effects of this variability, it is recommended that replicated concurrent analyses (randomized blocks) of groups of animals be used. That is, some samples from each of the groups of animals to be compared are analyzed at the same time. This process is replicated until a sufficient number of animals are sampled. If replicated concurrent analyses are not conducted and clinical measurements are made at different times for different groups of animals, the biases may be large. Clinical data were examined from several experiments to illustrate that the problems of clinical measurements are not confined to a particular endpoint, species, or sex. In one case, four times as many animals would have been required using nonconcurrent analyses to achieve the same precision as for concurrent analyses. Permutation analyses of two of the data sets indicate that statistical conclusions concerning the comparison of average clinical levels in different groups of animals would have been incorrect, falsely indicating higher or lower levels in a group over one-half of the time with nonconcurrent analyses.     

Developing protocols for in-water morphometric measurements of cetaceans using stereo-videogrammetry

Morphometry underpins the basic knowledge of any organism's population demographics and dynamics. Such understanding enables the investigation of trends with important conservation implications including monitoring the health of individuals and changes in population dynamics over time. By detecting declines in health prior to the onset of significant mortality, monitoring of body condition can potentially allow time for a management response to avert population decline. We trialed the use of a diver-operated stereo-video (SDOV) system for making morphometric measurements of dwarf minke whales (Balaenoptera acutorostrata subsp.), a small oceanic rorqual, in the Great Barrier Reef, Australia. The SDOV system produced 68% more precise replicate total body length measurements than a single-camera system, while both systems achieved a mean error below 0.5%. The increased precision offered by a SDOV system is desirable for longitudinal monitoring of growth rates and body condition. Optimal application of this method relied on adherence to protocols for both data collection and analysis beyond those dictated by the equipment user manuals. We provide recommendations for these field and analytical protocols, which may be suitable for use with other cetaceans when in-water access is available.     

A practical measuring system for intestinal pressure activity and its clinical application

AimTo propose a practical, non-invasive method for monitoring intestinal pressure activity and introduce its clinical application on discrimination between the healthy subjects and the slow transit constipation (STC) patient subjects in the sense of medical statistics.MethodsNineteen healthy subjects and eight STC patient subjects participated in the experiments. The authors tried to find the optimal feature combination by using the probabilistic neural network (PNN) to separate these two groups and test their significant differences.ResultsThe statistical analysis revealed that the combination of the frequency and the average pressure of the pressure activity induced by colonic peristalsis was the optimal feature combination among the possible feature subsets, which was composed of several typical extracted features, and the discrimination accuracy of test samples was about 88.89%. The one-way analysis of variance (ANOVA) analysis also showed that there were differences or significant differences between them.ConclusionsClinical experiments and analysis method related verified the practicability of the system, and the measurement technology developed for monitoring intestinal pressure activity was useful.     

Statistical methods for microarray assays

The paper shortly reviews statistical methods used in the area of DNA microarray studies. All stages of the experiment are taken into account: planning, data collection, data preprocessing, analysis and validation. Among the methods of data analysis, the algorithms for estimating differential expression, multivariate approaches, clustering methods, as well as classification and discrimination are reviewed. The need is stressed for routine statistical data processing protocols and for the search of links of microarray data analysis with quantitative genetic models.     

The clinical application of serial bone mass measurements

Although the short-term precision of various bone mineral content (BMC) measurements is known, questions about the clinical use of serial BMC measurements remain: how frequently should BMC be measured? When is it appropriate to calculate bone loss rates? How are estimates of loss rate interpreted? This paper discusses both biological and technical sources of uncertainty, and the estimation of confidence limits for measured bone loss rates. For many, possibly most, patients, calculation of bone loss rate may not be necessary; however, repeated measures of BMC can still be useful for re-evaluating fracture risk. Indications for repeating BMC measurements may include low initial BMC (moderate to high fracture risk), anticipation of rapid bone loss (e.g., menopause, estrogen discontinuation), and verification of treatment efficacy.     

Statistical methods for panel data from a semi-Markov process, with application to HPV

Continuous-time, multistate processes can be used to represent a variety of biological processes in the public health sciences; yet the analysis of such processes is complex when they are observed only at a limited number of time points. Inference methods for such panel data have been developed for time homogeneous Markov models, but there has been little research done for other classes of processes. We develop likelihood-based methods for panel data from a semi-Markov process, where transition intensities depend on the duration of time in the current state. The proposed methods account for possible misclassification of states. To illustrate the methods, we investigate a three- and a four-state models in detail and apply the results to model the natural history of oncogenic genital human papillomavirus infections in women.     

Statistical methods for detecting molecular adaptation

The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.     

Predicting biomass of Atlantic salmon from morphometric lateral measurements

Previously biomass predictions have been derived from simple weight—length relationships. This study measured a variety of truss and conventional dimensions covering the lateral body profile of Atlantic salmon Salmo salar and, using regression analysis, developed a series of multifactor weight—lateral dimension relationships. Single-factor regression equations proved inadequate for predicting weight with percentage errors between real and estimated values ranging from −1.2±6.8% to 72.5 ± 225.6%. Fifty-two multifactor regression equations were generated that predicted accurately the weight of individual fish to within ±2% using combinations of conventional and truss measurements. Regression coefficients were found to be significantly different ( P <0.05) between Scottish and Norwegian strains, indicating morphological differences between the genetic groups. Norwegian fish were generally heavier for a given length compared to Scottish strains. This suggests that morphologically different strains of S. salar would require individual weight: lateral dimension relationships to be developed in order to predict biomass accurately to within commercially acceptable levels.     

Statistical methods for ranking differentially expressed genes

In the analysis of microarray data the identification of differential expression is paramount. Here I outline a method for finding an optimal test statistic with which to rank genes with respect to differential expression. Tests of the method show that it allows generation of top gene lists that give few false positives and few false negatives. Estimation of the false-negative as well as the false-positive rate lies at the heart of the method.