Stability of gene contributions and identification of outliers in multivariate analysis of microarray data

BACKGROUND: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes. RESULTS: In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples. CONCLUSION: The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data

Two Novel Methods For The Determination Of The Number Of Components In Independent Components Analysis Models

Independent Components Analysis is a Blind Source Separation method that aims to find the pure source signals mixed together in unknown proportions in the observed signals under study. It does this by searching for factors which are mutually statistically independent. It can thus be classified among the latent-variable based methods. Like other methods based on latent variables, a careful investigation has to be carried out to find out which factors are significant and which are not. Therefore, it is important to dispose of a validation procedure to decide on the optimal number of independent components to include in the final model. This can be made complicated by the fact that two consecutive models may differ in the order and signs of similarly-indexed ICs. As well, the structure of the extracted sources can change as a function of the number of factors calculated. Two methods for determining the optimal number of ICs are proposed in this article and applied to simulated and real datasets to demonstrate their performance

Central motor control failure in fibromyalgia: a surface electromyography study

<p>Abstract</p> <p>Background</p> <p>Fibromyalgia (FM) is characterised by diffuse musculoskeletal pain and stiffness at multiple sites, tender points in characteristic locations, and the frequent presence of symptoms such as fatigue. The aim of this study was to assess whether the myoelectrical manifestations of fatigue in patients affected by FM are central or peripheral in origin.</p> <p>Methods</p> <p>Eight female patients aged 55.6 ± 13.6 years (FM group) and eight healthy female volunteers aged 50.3 ± 9.3 years (MCG) were studied by means of non-invasive surface electromyography (s-EMG) involving a linear array of 16 electrodes placed on the skin overlying the biceps brachii muscle, with muscle fatigue being evoked by means of voluntary and involuntary (electrically elicited) contractions. Maximal voluntary contractions (MVCs), motor unit action potential conduction velocity distributions (mean ± SD and skewness), and the mean power frequency of the spectrum (MNF) were estimated in order to assess whether there were any significant differences between the two groups and contraction types.</p> <p>Results</p> <p>The motor pattern of recruitment during voluntary contractions was altered in the FM patients, who also showed fewer myoelectrical manifestations of fatigue (normalised conduction velocity rate of changes: -0.074 ± 0.052%/s in FM vs -0.196 ± 0.133%/s in MCG; normalised MNF rate of changes: -0.29 ± 0.16%/s in FM vs -0.66 ± 0.34%/s in MCG). Mean conduction velocity distribution and skewnesses values were higher (p < 0.01) in the FM group. There were no between-group differences in the results obtained from the electrically elicited contractions.</p> <p>Conclusion</p> <p>The apparent paradox of fewer myoelectrical manifestations of fatigue in FM is the electrophysiological expression of muscle remodelling in terms of the prevalence of slow conducting fatigue-resistant type I fibres. As the only between-group differences concerned voluntary contractions, they are probably more related to central motor control failure than muscle membrane alterations, which suggests pathological muscle fibre remodelling related to altered suprasegmental control.</p