BACKGROUND: There are many sources of variation in dual labelled microarray experiments, including data acquisition and image processing. The final interpretation of experiments strongly relies on the accuracy of the measurement of the signal intensity. For low intensity spots in particular, accurately estimating gene expression variations remains a challenge as signal measurement is, in this case, highly subject to fluctuations. RESULTS: To evaluate the fluctuations in the fluorescence intensities of spots, we used series of successive scans, at the same settings, of whole genome arrays. We measured the decrease in fluorescence and we evaluated the influence of different parameters (PMT gain, resolution and chemistry of the slide) on the signal variability, at the level of the array as a whole and by intensity interval. Moreover, we assessed the effect of averaging scans on the fluctuations. We found that the extent of photo-bleaching was low and we established that 1) the fluorescence fluctuation is linked to the resolution e.g. it depends on the number of pixels in the spot 2) the fluorescence fluctuation increases as the scanner voltage increases and, moreover, is higher for the red as opposed to the green fluorescence which can introduce bias in the analysis 3) the signal variability is linked to the intensity level, it is higher for low intensities 4) the heterogeneity of the spots and the variability of the signal and the intensity ratios decrease when two or three scans are averaged. CONCLUSION: Protocols consisting of two scans, one at low and one at high PMT gains, or multiple scans (ten scans) can introduce bias or be difficult to implement. We found that averaging two, or at most three, acquisitions of microarrays scanned at moderate photomultiplier settings (PMT gain) is sufficient to significantly improve the accuracy (quality) of the data and particularly those for spots having low intensities and we propose this as a general approach. For averaging and precise image alignment at sub-pixel levels we have made a program freely available on our web-site http://bioinfome.cgm.cnrs-gif.fr to facilitate implementation of this approach.

UNLABELLED: MAnGO (Microarray Analysis at the Gif/Orsay platform) is an interactive R-based tool for the analysis of two-colour microarray experiments. It is a compilation of various methods, which allows the user (1) to control data quality by detecting biases with a large number of visual representations, (2) to pre-process data (filtering and normalization) and (3) to carry out differential analyses. MAnGO is not only a 'turn-key' tool, oriented towards biologists but also a flexible and adaptable R script oriented towards bioinformaticians. AVAILABILITY: http://bioinfome.cgm.cnrs-gif.fr/.

MOTIVATION: Two-colour microarrays are widely used to perform transcriptome analysis. In most cases, it appears that the 'red' and 'green' images resulting from the scan of a microarray slide are slightly shifted one with respect to the other. To increase the robustness of the measurement of the fluorescent emission intensities, multiple acquisitions with the same or different PMT gains can be used. In these cases, a systematic correction of image shift is required. RESULTS: To accurately detect this shift, we first developed an approach using cross-correlation. Second, we evaluated the most appropriate interpolation method to be used to derive the registered image. Then, we quantified the effects of image shifts on spot quality, using two different quality estimators. Finally, we measured the benefits associated with a systematic image registration. In this study, we demonstrate that registering the two images prior to data extraction provides a more reliable estimate of the two colours' ratio and thus increases the accuracy of measurements of variations in gene expression. AVAILABILITY: http://bioinfome.cgm.cnrs-gif.fr/.

A program package has been developed to align automatically images of biological objects containing an n-fold symmetry, and to remove the distortions induced on their circular shape by the microtomy. It uses an original procedure based on correlation techniques and replaces usual manual processing. Examples of direct averaging of transverse sections of biological objects are given to illustrate the program's capabilities.