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PubMed2006

Robust trend tests for genetic association using matched case-control design.

Trend tests for genetic association using a matched case-control design are studied, which allows for a variable number of controls per case. However, the tests depend on the scores based on the underlying genetic model, thus it may result in substantial loss of power when the model is misspecified. Since the mode of inheritance may be unknown for complex diseases, robust trend tests in matched case-control studies are developed. Simulation is conducted to compare the trend tests and the robust trend tests under various genetic models. The results are applied to detect candidate-gene association using an example from a case-control aetiologic study of sarcoidosis.

Black People↗

PubMed2007

Multiple linear regression with some correlated errors: classical and robust methods.

In this paper we consider classical and robust methods of estimation and diagnostics for the multiple linear regression model when some of the errors are correlated. This work was motivated by the analysis of a medical data set, from an observational study aimed at identifying factors affecting the outcome of a surgical method for the correction of scoliosis (abnormal lateral spinal curvature). There are 392 observations but some of them are on the same patient (double curves). It seems adequate to consider a multiple linear regression model but, since it is not desirable to discard the double curves, the assumption of non-correlated errors is clearly violated, and this is indeed confirmed by related diagnostics on the residuals (Durbin-Watson test). A more appropriate model retains the linear structure but allows for non-null correlation between the errors on the same patient. We propose two different procedures for the estimation of the parameters of the linear model and the correlation parameters: maximum likelihood assuming normal errors and a robustified version obtained by plugging-in results from robust linear regression. The latter procedure is designed to be resistant to outlying observations or error distributions with heavy tails and has produced the most satisfactory results for the analysed data set.

Data Interpretation, Statistical↗

PubMedDate not supplied

Robustness of the two independent samples t-test when applied to ordinal scaled data.

One may encounter the application of the two independent samples t-test to ordinal scaled data (for example, data that assume only the values 0, 1, 2, 3) from small samples. This situation clearly violates the underlying normality assumption for the t-test and one cannot appeal to large sample theory for validity. In this paper we report the results of an investigation of the t-test's robustness when applied to data of this form for samples of sizes 5 to 20. Our approach consists of complete enumeration of the sampling distributions and comparison of actual levels of significance with the significance level expected if the data followed a normal distribution. We demonstrate under general conditions the robustness of the t-test in that the maximum actual level of significance is close to the declared level.

Biometry↗

PubMed2001

Assessing the robustness of randomization tests: examples from behavioural studies.

Behavioural studies are commonly plagued with data that violate the assumptions of parametric statistics. Consequently, classic nonparametric methods (e.g. rank tests) and novel distribution-free methods (e.g. randomization tests) have been used to a great extent by behaviourists. However, the robustness of such methods in terms of statistical power and type I error have seldom been evaluated. This probably reflects the fact that empirical methods, such as Monte Carlo approaches, are required to assess these concerns. In this study we show that analytical methods cannot always be used to evaluate the robustness of statistical tests, but rather Monte Carlo approaches must be employed. We detail empirical protocols for estimating power and type I error rates for parametric, nonparametric and randomization methods, and demonstrate their application for an analysis of variance and a regression/correlation analysis design. Together, this study provides a framework from which behaviourists can compare the reliability of different methods for data analysis, serving as a basis for selecting the most appropriate statistical test given the characteristics of data at hand. Copyright 2001 The Association for the Study of Animal Behaviour.

Journal Article↗

PubMed1994

Fibroblasts genetically modified to produce nerve growth factor induce robust neuritic ingrowth after grafting to the spinal cord.

The influences of neurotrophic factors on adult mammalian spinal cords are incompletely understood. In the present experiment, we utilized somatic gene transfer to examine the effects of nerve growth factor (NGF) on the unlesioned spinal cords of adult Fischer rats. Fischer 344 rat primary fibroblasts were genetically modified in vitro to produce and secrete NGF, then grafted to spinal cords at the T7 level. Grafts survived in vivo for periods of up to 1 year, and induced an extremely robust ingrowth of spinal neurites. Control and basic fibroblast growth factor-producing grafts did not promote extensive neurite growth. Neurites penetrating the NGF grafts were of sensory origin, since they labeled immunocytochemically for calcitonin gene-related peptide but not markers of other neuronal transmitter phenotypes. Electron microscopy revealed that neurites within NGF-secreting grafts were enveloped in glial cell processes and that axons frequently became myelinated. These results indicate that (i) genetically modified cell grafts are a useful model for studying trophic factor effects in the adult mammalian spinal cord, (ii) sensory neurites maintain robust NGF responsiveness into adulthood, and (iii) sprouting neurites can follow glial channels and become myelinated in the adult spinal cord. Grafts of fibroblasts genetically modified to secrete trophic factors merit study as potential tools for promoting regeneration after spinal cord injury.

Animals↗

PubMed1997

Robust growth of chronically injured spinal cord axons induced by grafts of genetically modified NGF-secreting cells.

Little spontaneous regeneration of axons occurs after acute and chronic injury to the CNS. Previously we have shown that the continuous local delivery of neurotrophic factors to the acutely injured spinal cord induces robust growth of spinal and supraspinal axons. In the present study we examined whether chronically injured axons also demonstrate significant neurotrophin responsiveness. Adult rats underwent bilateral dorsal hemisection lesions that axotomize descending supraspinal pathways, including the corticospinal, rubrospinal, and cerulospinal tracts, and ascending dorsal spinal sensory projections. One to three months later, injured rats received grafts of syngenic fibroblasts genetically modified to produce nerve growth factor (NGF). Control subjects received unmodified cell grafts or cells transduced to express the reporter gene beta-galactosidase. Three to five months after grafting, animals that received NGF-secreting grafts showed dense growth of putative cerulospinal axons and primary sensory axons of the dorsolateral fasciculus into the grafted lesion site. Growth from corticospinal, raphaespinal, and local motor axons was not detected. Thus, robust growth of defined populations of supraspinal and spinal axons can be elicited in chronic stages after spinal cord injury by localized, continuous transgenic delivery of neurotrophic factors.

Animals↗

PubMed1997

Visible volume: a robust measure for protein structure characterization.

We propose a new characterization of protein structure based on the natural tetrahedral geometry of the beta-carbon and a new geometric measure of structural similarity, called visible volume. In our model, the side-chains are replaced by an ideal tetrahedron, the orientation of which is fixed with respect to the backbone and corresponds to the preferred rotamer directions. Visible volume is a measure of the non-occluded empty space surrounding each residue position after the side-chains have been removed. It is a robust, parameter-free, locally computed quantity that accounts for many of the spatial constraints that are of relevance to the corresponding position in the native structure. When computing visible volume, we ignore the nature of both the residue observed at each side and the ones surrounding it. We focus instead on the space that, together, these residues could occupy. By doing so, we are able to quantify a new kind of invariance beyond the apparent variations within protein families, namely, the conservation of the physical space available at structurally equivalent positions for side-chain packing. Corresponding positions in native structures are likely to be of interest in protein structure prediction, protein design, and homology modeling. Visible volume is related to the degree of exposure of a residue position and to the actual rotamers in native proteins. Here, we discuss the properties of this new measure, namely, its robustness with respect to both crystallographic uncertainties and naturally occurring variations in atomic coordinates, and the remarkable fact that it is essentially independent of the choice of the parameters used in calculating it. We also show how visible volume can be used to align protein structures, to identify structurally equivalent positions that are conserved in a family of proteins, and to single out positions in a protein that are likely to be of biological interest. These properties qualify visible volume as a powerful tool in a variety of applications, from the detailed analysis of protein structure to homology modeling, protein structural alignment, and the definition of better scoring functions for threading purposes.

Animals↗

PubMed1999

Isologous diversification for robust development of cell society.

Isologous diversification, proposed for cell differentiation, is shown to be stable against molecular and other external fluctuations, where amplification of noise-induced slight difference between cells leads to a noise-tolerant society with differentiated cell types. It is a general consequence of interacting cells with biochemical networks and cell divisions, as is confirmed by several model simulations. According to the theory, differentiation proceeds first by loss of synchrony of intracellular oscillations as the number of cells increases. Then the chemical composition of the cells is differentiated. The differentiated compositions become inherited by the next generation, and lead to determined cell types. As a result of successive occurrence of the cell differentiation, the cell society will be composed of different cell types. The whole developmental process is robust not only against molecular fluctuations but also against the removal of a cluster of cells. This robustness is a remarkable feature of isologous diversification, in contrast to the conventional threshold-type mechanism for development. As a testable consequence of the theory, we also discuss interaction-dependent tumor formation and negative correlation between growth speed and chemical diversity.

Animals↗

PubMed2002

Robustness as a measure of plausibility in models of biochemical networks.

Theory, experiment, and observation suggest that biochemical networks which are conserved across species are robust to variations in concentrations and kinetic parameters. Here, we exploit this expectation to propose an approach to model building and selection. We represent a model as a mapping from parameter space to behavior space, and utilize bifurcation analysis to study the robustness of each region of steady-state behavior to parameter variations. The hypothesis that potential errors in models will result in parameter sensitivities is tested by analysis of two models of the biochemical oscillator underlying the Xenopus cell cycle. Our analysis successfully identifies known weaknesses in the older model and suggests areas for further investigation in the more recent, more plausible model. It also correctly highlights why the more recent model is more plausible.

Animals↗

PubMed2002

Accurate, robust, and automated longitudinal and cross-sectional brain change analysis.

Quantitative measurement of brain size, shape, and temporal change (for example, in order to estimate atrophy) is increasingly important in biomedical image analysis applications. New methods of structural analysis attempt to improve robustness, accuracy, and extent of automation. A fully automated method of longitudinal (temporal change) analysis, SIENA, was presented previously. In this paper, improvements to this method are described, and also an extension of SIENA to a new method for cross-sectional (single time point) analysis. The methods are fully automated, robust, and accurate: 0.15% brain volume change error (longitudinal): 0.5-1% brain volume accuracy for single-time point (cross-sectional). A particular advantage is the relative insensitivity to differences in scanning parameters. The methods provide easy manual review of their output by the automatic production of summary images which show the results of the brain extraction, registration, tissue segmentation, and final atrophy estimation.

Algorithms↗

PubMed2005

Hybrid formulation of the model-based non-rigid registration problem to improve accuracy and robustness.

We present a new algorithm to register 3D pre-operative Magnetic Resonance (MR) images with intra-operative MR images of the brain. This algorithm relies on a robust estimation of the deformation from a sparse set of measured displacements. We propose a new framework to compute iteratively the displacement field starting from an approximation formulation (minimizing the sum of a regularization term and a data error term) and converging toward an interpolation formulation (least square minimization of the data error term). The robustness of the algorithm is achieved through the introduction of an outliers rejection step in this gradual registration process. We ensure the validity of the deformation by the use of a biomechanical model of the brain specific to the patient, discretized with the finite element method. The algorithm has been tested on six cases of brain tumor resection, presenting a brain shift up to 13 mm.

Algorithms↗

PubMed1987

OMNE: a new robust membership-set estimator for the parameters of nonlinear models.

A new method for estimating parameters and their uncertainty is presented. Data are assumed to be corrupted by a noise whose statistical properties are unknown but for which bounds are available at each sampling time. The method estimates the set of all parameter vectors consistent with this hypothesis. Its results are compared with those of the weighted least squares, extended least squares, and biweight robust regression approaches on two data sets, one of which includes 33% outliers. On the basis of these preliminary results, the new method appears to have attractive properties of reliability and robustness.

Kinetics↗

PubMed1988

Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

Animal Testing Alternatives↗

PubMed1981

[ROBETH: a library for robust statistical procedures].

In the past 20 years the theory of robust estimation has become an important topic of mathematical statistics. We discuss here some basic concepts of this theory with the help of simple examples. Furthermore we describe a subroutine library for the application of robust statistical procedures, which was developed with the support of the Swiss National Science Foundation.

Humans↗

PubMed1991

Robustness of maximum likelihood tree estimation against different patterns of base substitutions.

In the maximum likelihood (ML) method for estimating a molecular phylogenetic tree, the pattern of nucleotide substitutions for computing likelihood values is assumed to be simpler than that of the actual evolutionary process, simply because the process, considered to be quite devious, is unknown. The problem, however, is that there has been no guarantee to endorse the simplification. To study this problem, we first evaluated the robustness of the ML method in the estimation of molecular trees against different nucleotide substitution patterns, including Jukes and Cantor's, the simplest ever proposed. Namely, we conducted computer simulations in which we could set up various evolutionary models of a hypothetical gene, and define a true tree to which an estimated tree by the ML method was to be compared. The results show that topology estimation by the ML method is considerably robust against different ratios of transitions to transversions and different GC contents, but branch length estimation is not so. The ML tree estimation based on Jukes and Cantor's model is also revealed to be resistant to GC content, but rather sensitive to the ratio of transitions to transversions. We then applied the ML method with different substitution patterns to nucleotide sequence data on tax gene from T-cell leukemia viruses whose evolutionary process must have been more complicated than that of the hypothetical gene. The results are in accordance with those from the simulation study, showing that Jukes and Cantor's model is as useful as a more complicated one for making inferences about molecular phylogeny of the viruses.

Base Composition↗

PubMed2004

Robust simple sequence repeat markers for spruce (Picea spp.) from expressed sequence tags.

Traditionally, simple sequence repeat (SSR)markers have been developed from libraries of genomic DNA. However, the large, repetitive nature of conifer genomes makes development of robust, single-copy SSR markers from genomic DNA difficult. Expressed sequence tags (ESTs), or sequences of messenger RNA, offer the opportunity to exploit single, low-copy, conserved sequence motifs for SSR development. From a 20,275-unigene spruce EST set, we identified 44 candidate EST-SSR markers. Of these, 25 amplified and were polymorphic in white, Sitka, and black spruce; 20 amplified in all 3 spruce species tested; the remaining five amplified in all except one species. In addition, 101 previously described spruce SSRs (mostly developed from genomic DNA), were tested. Of these, 17 amplified across white,Sitka, and black spruce. The 25 EST-SSRs had approximately 9% less heterozygosity than the 17 genomic-derived SSRs (mean H=0.65 vs 0.72), but appeared to have less null alleles, as evidenced by much lower apparent inbreeding (mean F=0.046 vs 0.126). These robust SSRs are of particular use in comparative studies,and as the EST-SSRs are within the expressed portion of the genome, they are more likely to be associated with a particular gene of interest, improving their utility for quantitative trait loci mapping and allowing detection of selective sweeps at specific genes.

Base Sequence↗

PubMed2002

A study of method robustness for arsenic speciation in drinking water samples by anion exchange HPLC-ICP-MS.

Regulating arsenic species in drinking waters is a reasonable objective, since the various species have different toxicological impacts. However, developing robust and sensitive speciation methods is mandatory prior to any such regulations. Numerous arsenic speciation publications exist, but the question of robustness or ruggedness for a regulatory method has not been fully explored. The present work illustrates the use of anion exchange chromatography coupled to ICP-MS with a commercially available "speciation kit" option. The mobile phase containing 2 mM NaH(2)PO(4) and 0.2 mM EDTA at pH 6 allowed adequate separation of four As species (As(III), As(V), MMAA, DMAA) in less than 10 min. The analytical performance characteristics studied, including method detection limits (lower than 100 ng L(-1) for all the species evaluated), proved the suitability of the method to fulfill the current regulation. Other parameters evaluated such as laboratory fortified blanks, spiked recoveries, and reproducibility over a certain period of time produced adequate results. The samples analyzed were taken from water utilities in different areas of the United States and were provided by the U.S. EPA. The data suggests the speciation setup performs to U.S. EPA specifications but sample treatment and chemistry are also important factors for achieving good recoveries for samples spiked with As(III) as arsenite and As(V) as arsenate.

Arsenic↗

PubMed2004

The robustness of naturally and artificially selected nucleic acid secondary structures.

Thermodynamic stability and mutational robustness of secondary structure are critical to the function and evolutionary longevity of RNA molecules. We hypothesize that natural and artificial selection for functional molecules favors the formation of structures that are stable to both thermal and mutational perturbation. There is little direct evidence, however, that functional RNA molecules have been selected for their stability. Here we use thermodynamic secondary structure prediction algorithms to compare the thermal and mutational robustness of over 1000 naturally and artificially evolved molecules. Although we find evidence for the evolution of both types of stability in both sets of molecules, the naturally evolved functional RNA molecules were significantly more stable than those selected in vitro, and artificially evolved catalysts (ribozymes) were more stable than artificially evolved binding species (aptamers). The thermostability of RNA molecules bred in the laboratory is probably not constrained by a lack of suitable variation in the sequence pool but, rather, by intrinsic biases in the selection process.

Base Composition↗