UNLABELLED: Xdigitise is a software system for visualization of hybridization experiments giving the user facilities to analyze the corresponding images manually or automatically. Images of the high-density DNA arrays are displayed as well as the results of an external image analysis bundled with Xdigitise, e.g. the spot locations are marked and the duplicate correlations are shown by a color scale. AVAILABILITY: Xdigitise can be downloaded from http://www.molgen.mpg.de/~xdigitise.

BACKGROUND: Gene expression analyses based on complex hybridization measurements have increased rapidly in recent years and have given rise to a huge amount of bioinformatic tools such as image analyses and cluster analyses. However, the amount of work done to integrate and evaluate these tools and the corresponding experimental procedures is not high. Although complex hybridization experiments are based on a data production pipeline that incorporates a significant amount of error parameters, the evaluation of these parameters has not been studied yet in sufficient detail. RESULTS: In this paper we present simulation studies on several error parameters arising in complex hybridization experiments. A general tool was developed that allows the design of exactly defined hybridization data incorporating, for example, variations of spot shapes, spot positions and local and global background noise. The simulation environment was used to judge the influence of these parameters on subsequent data analysis, for example image analysis and the detection of differentially expressed genes. As a guide for simulating expression data real experimental data were used and model parameters were adapted to these data. Our results show how measurement error can be balanced by the analysis tools. CONCLUSIONS: We describe an implemented model for the simulation of DNA-array experiments. This tool was used to judge the influence of critical parameters on the subsequent image analysis and differential expression analysis. Furthermore the tool can be used to guide future experiments and to improve performance by better experimental design. Series of simulated images varying specific parameters can be downloaded from our web-site: http://www.molgen.mpg.de/~lh_bioinf/projects/simulation/biotech/

MOTIVATION: Image analysis is a major part of data evaluation for array hybridization experiments in molecular biology. The program presented here is designed to analyze automatically images from hybridization experiments with various arrangements: different kinds of probes (oligonucleotides or complex probes), different supports (nylon filters or glass slides), different labeling of probes (radioactively or fluorescently). The program is currently applied to oligonucleotide fingerprinting projects and complex hybridizations. The only precondition for the use of the program is that the targets are arrayed in a grid, which can be approximately transformed to an orthogonal equidistant grid by a projective mapping. RESULTS: We demonstrate that our program can cope with the following problems: global distortion of the grid, missing of grid nodes, local deviation of the spot from its specified grid position. This is checked by different quality measures. The image analysis of oligonucleotide fingerprint experiments on an entire genetic library is used, in clustering procedures, to group related clones together. The results show that the program yields automatically generated high quality input data for follow up analysis such as clustering procedures. AVAILABILITY: The executable files will be available upon request for academics.

MOTIVATION: The choice of probes is an important feature of hybridisation experiments. In this paper we present an algorithm that optimises probes with respect to a training set of sequences based on Shannon entropy as a quality criterion. The practical motivation for our algorithm is oligonucleotide fingerprinting, a method for the simultaneous identification of sequences (cDNA or genomic DNA) by their hybridisation tags according to a set of short probes such as octamers, although the algorithm is of course not restricted to that application. RESULTS: We can show that our method is superior to the selection of probes according to their frequencies, which is a widely used strategy, and to randomly chosen probe sets. The quality of probe sets is assessed by a simulation pipeline that entails the set of probes as a simulation parameter. The performance of probe sets trained on sequences from different organisms shows additionally that probes should be chosen with regard to the organism under analysis. Case studies are presented on how constraints (G+C-content, complexity of the individual probes) influence the selection process. AVAILABILITY: A description of the oligonucleotide fingerprinting pipeline is published on our web-page http://www.molgen.mpg.de/ approximately ag_onf/met.htm. An executable of the algorithm and probe lists designed for human and rodents can be downloaded from the ftp-site ftp://ftp.molgen.mpg.de/pub/mpimg/probe_design/.