Research article

Simulation of DNA array hybridization experiments and evaluation of critical parameters during subsequent image and data analysis

Christoph K Wierling¹ , Matthias Steinfath¹ , Thorsten Elge² , Steffen Schulze-Kremer² , Pia Aanstad³ , Matthew Clark¹ , Hans Lehrach¹ and Ralf Herwig¹

¹  Department of Vertebrate Genomics, Max-Planck-Institut für Molekulare Genetik, Ihnestrasse 73, D-14195 Berlin-Dahlem, Germany

²  Deutsches Ressourcenzentrum für Genomforschung GmbH, Heubnerweg 6, D-14059 Berlin, Germany

³  Department of Biochemistry, University of California, San Francisco, 513 Parnassus Ave, San Francisco, CA-94143-0448, USA

author email corresponding author email

BMC Bioinformatics 2002, 3:29doi:10.1186/1471-2105-3-29

Published:	22 October 2002

Abstract

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/ webcite