Biomedical subjects

Ernst Wit

Publications and source records attributed to Ernst Wit.

4 recordsLinked to original sources

PubMed2005

Transcriptional profiling of tissue plasticity: role of shifts in gene expression and technical limitations.

Reprogramming of gene expression has been recognized as a main instructive modality for the adjustments of tissues to various kinds of stress. The recent application of gene expression profiling has provided a powerful tool to elucidate the molecular pathways underlying such tissue remodeling. However, the biological interpretations of expression profiling results critically depend on normalization of transcript signals to mRNA standards before statistical evaluation. A hypothesis is proposed whereby the "fluctuating nature" of gene expression represents an inherent limitation of the test system used to quantify RNA levels. Misinterpretation of gene expression data occurs when RNA quantities are normalized to a subset of mRNAs that are subject to strong regulation. The contention of contradictory biological outcomes using different RNA-normalization schemes is demonstrated in two models of skeletal muscle plasticity with data from custom-designed microarrays and biochemical and ultrastructural evidence for correspondingly altered RNA content and nucleolar activity. The prevalence of these biological constraints is underlined by a literature survey in different models of tissue plasticity with emphasis on the unique malleability of skeletal muscle. Finally, recommendations on the optimal experimental layout are given to control biological and technical variability in microarray and RT-PCR studies. It is proposed to approach normalization of transcript signals by measuring total RNA and DNA content per sample weight and by correcting for concurrently estimated endogenous standards such as major ribosomal RNAs and spiked RNA and DNA species. This allows for later conversion to diverse tissue-relevant references and should improve the physiological interpretations of phenotypic plasticity.

Adaptation, Physiological↗

PubMed2005

Design of large time-course microarray experiments with two channels.

In this article we propose two practical types of designs for large time-course, dual-channel microarray experiments. One type consists of several interwoven loops, and the other type combines reference and loop designs. By representing the experiment as a graph, where the timepoints are nodes and the arrays are edges, we demonstrate how the time contrasts between any two timepoints can be estimated, provided that there is a path of edges linking them. In addition, we give a general formula for the variance of such contrasts. The efficiency of the proposed designs is evaluated by estimating the variances of the log-ratios of the comparisons of interest.

Journal Article↗

PubMed2004

Weighted analysis of microarray gene expression using maximum-likelihood.

MOTIVATION: The numerical values of gene expression measured using microarrays are usually presented to the biological end-user as summary statistics of spot pixel data, such as the spot mean, median and mode. Much of the subsequent data analysis reported in the literature, however, uses only one of these spot statistics. This results in sub-optimal estimates of gene expression levels and a need for improvement in quantitative spot variation surveillance. RESULTS: This paper develops a maximum-likelihood method for estimating gene expression using spot mean, variance and pixel number values available from typical microarray scanners. It employs a hierarchical model of variation between and within microarray spots. The hierarchical maximum-likelihood estimate (MLE) is shown to be a more efficient estimator of the mean than the 'conventional' estimate using solely the spot mean values (i.e. without spot variance data). Furthermore, under the assumptions of our model, the spot mean and spot variance are shown to be sufficient statistics that do not require the use of all pixel data. The hierarchical MLE method is applied to data from both Monte Carlo (MC) simulations and a two-channel dye-swapped spotted microarray experiment. The MC simulations show that the hierarchical MLE method leads to improved detection of differential gene expression particularly when 'outlier' spots are present on the arrays. Compared with the conventional method, the MLE method applied to data from the microarray experiment leads to an increase in the number of differentially expressed genes detected for low cut-off P-values of interest.

Algorithms↗

PubMed2003

Statistical adjustment of signal censoring in gene expression experiments.

MOTIVATION: Numerical output of spotted microarrays displays censoring of pixel intensities at some software dependent threshold. This reduces the quality of gene expression data, because it seriously violates the linearity of expression with respect to signal intensity. Statistical methods based on typically available spot summaries together with some parametric assumptions can suggest ways to correct for this defect. RESULTS: A maximum likelihood approach is suggested together with a sensible approximation to the joint density of the mean, median and variance-which are typically available to the biological end-user. The method 'corrects' the gene expression values for pixel censoring. A by-product of our approach is a comparison between several two-parameter models for pixel intensity values. It suggests that pixels separated by one or two other pixels can be considered independent draws from a Lognormal or a Gamma distribution. AVAILABILITY: The R/S-Plus code is available at http://www.stats.gla.ac.uk/~microarray/software.

Algorithms↗