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Bioinformatics Advance Access originally published online on September 22, 2005
Bioinformatics 2005 21(22):4194-4195; doi:10.1093/bioinformatics/bti686
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oxfordjournals.org

Doelan: a solution for quality control monitoring of microarray production

Laurent Jourdren 1 and Stéphane Le Crom 1,2,*

1IFR36, Plate-forme Transcriptome 46 rue d'Ulm, 75230 Paris cedex05, France
2INSERM U368, École Normale Supérieure 46 rue d'Ulm, 75230 Paris cedex05, France

*To whom correspondence should be addressed.


   ABSTRACT
TOP
 ABSTRACT
1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
 4 PRACTICAL USE
 5 CONCLUSION
 REFERENCES
 

Summary: Doelan is an automated tool designed to monitor the quality of DNA microarray production. The software executes a series of quality control tests on hybridizations to validate batches of chips. The reports generated by Doelan should help microarray platforms aiming at quality labels, such as ISO 9001 certification. The Doelan application is written in Java and works with a plug-in system that allows everyone to add custom validation tests.

Availability: The Doelan application is distributed under the GNU General Public License at http://transcriptome.ens.fr/doelan/

Contact: lecrom{at}biologie.ens.fr

Supplementary information: Complete documentation, source code and screenshots are available at http://transcriptome.ens.fr/doelan/


   1 INTRODUCTION
TOP
 ABSTRACT
 1 INTRODUCTION
2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
 4 PRACTICAL USE
 5 CONCLUSION
 REFERENCES
 
Production of glass slide microarrays requires the spotting of a large number of probes. In this process, many factors can influence the success of the spotting (i.e. blocked spotting pin, glass slides surface treatment, environment conditions); and controlling the quality of the spotting process is thus a prerequisite before distributing chips to the final user. A number of reports on quality control of microarrays are available, but they mainly focus on image analysis and how a spot can be used for quantification (Hautaniemi et al., 2003; Sauer et al., 2005); or on quality control of microarrays once real hybridization has already been done (Model et al., 2002; Tran et al., 2002; Buness et al., 2005; Reimers and Weinstein, 2005). From our knowledge, nobody works on quality control of microarray production before slide distribution to the final user for hybridization.

On a microarray platform, the microarray quality control manager takes a number of chips from one batch for validation, using various quality controls, such as sybergreen (whole labelling of nucleic acids; Shearstone et al., 2002; Hessner et al., 2004), self-hybridization experiments (the same RNA samples labelled with two dyes in both ways) or reference experiments for differential analysis. Taking the decision of validating a batch of chips is difficult, as many different parameters such as spot diameter, heterogeneous or absent spots have to be manually considered. In addition, spotting validation is a very subjective step so that the opinion about a batch may differ between two quality control managers. Using manually defined criteria for microarray quality, Doelan now allows an automated expertise of the quality of a batch of slides and automatically makes the decision of validating or rejecting a batch. Doelan also creates an output file describing batch quality.


   2 DOELAN PRINCIPLE AND IMPLEMENTATION
TOP
 ABSTRACT
 1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
3 AVAILABLE TESTS
 4 PRACTICAL USE
 5 CONCLUSION
 REFERENCES
 
The principle of Doelan is based on a series of test, each test being dedicated to a specific task applied to each spot on the microarray image (e.g. the verification of spot diameter). The microarray designer creates a series of tests and defines the parameters of each test to validate a chip (i.e. minimal and maximal values for spot diameter, thresholds for the acceptable number of spots). Dedicated series of tests can be created according to the type of validation experiment chosen, for instance, sybergreen, universal RNA hybridization or a reference experiment (Fig. 1). The failure of one test leads to the failure of the entire series of test, and consequently to the rejection of the whole batch of chips.



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  		Fig. 1 How to use Doelan, a working example. This example is based on a microarray platform producing a whole genome mouse microarray. When a slide is used to test the quality of a new batch, the image analysis performed by Genepix gives a result file (.GPR), which is used as an input to Doelan. The GPR file is an array where each row represents a spot and each column the information about spots gathered by the GenePix image analysis software. In Doelan, the user loads this GPR file, selects the associated series of tests and runs the tests. Here, for each batch of slide, two types of quality controls are performed, one sybergreen labelling and one self-hybridization experiment. For each quality control various tests (Test1, Test2, Test3) are applied. For the same Test (e.g. Test2), different parameters can be set for each quality control. For example, the threshold for total number of not-found spots to be accepted is set to 5% of the total number of spots in the sybergreen labelling test series and to 10% in the self-hybridization experiment test series. Doelan output a report in which each test is performed on the input file and displays the result, which indicates if the test was successful or if it failed. Optionally, a gene array list (.GAL file) can be loaded in Doelan together with the GPR file, allowing the creation of a corrected GAL file that takes into account the results of the tests. This GAL file reflects the localization of each spots on the slide surface and is used as a scaffold by GenePix image analysis software. Dotted arrows indicate an optional input or output.

 
Doelan is easy to use and install locally by biologists. It can be integrated within the Genepix window used to display report on results or run as an independent application on various operating systems (Windows, Mac OS X and Linux). The Doelan graphical user interface was developed using the Java programming language and is published under the GNU General Public License for the main application and under the GNU Lesser General Public License for the underlying library.


   3 AVAILABLE TESTS
TOP
 ABSTRACT
 1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
4 PRACTICAL USE
 5 CONCLUSION
 REFERENCES
 
Doelan is already bundled with many tests. Each test can deal with various properties of the microarray spots, such as diameter, intensity, flags from Genepix image analysis software, heterogeneity, saturated pixels and so on. A global test is also available to provide information about sets of independent tests results. This test only reports on the number of spots which have failed to pass one or more tests as for instance, a spot could be rejected because of the number of saturated pixels and because of its heterogeneity. A complete list of tests available in Doelan is given in the Supplementary information. In addition to these standard tests, the Doelan plug-in system based on Java facilitates the integration of custom test to fulfil specific needs.


   4 PRACTICAL USE
TOP
 ABSTRACT
 1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
 4 PRACTICAL USE
5 CONCLUSION
 REFERENCES
 
Doelan first requires that the user performs image analysis on the experiment made for quality control, before starting a series of test. Next the user selects the series of test adapted to the type of microarray and to the quality control hybridization performed (Fig. 1). This test series gathers all the tests relevant for a specific analysis. After launching the test series, Doelan generates a report that first displays general information about the test series and summaries all the results obtained from the application. Next, the report provides detailed information about all the tests including parameters, results, comments and graphs to help visualize the information as for example, spot diameter distribution. The last part of the report is available only if an optional array list file was loaded with the result file. This file provides information about the slide layout as the number of spot blocks and their localization on the slide surface. The spot map displayed in Doelan report represents the locations of the spots on the microarray that passed the tests (in green) and which did not (in red). Furthermore, if this option was chosen, it allows the creation of an output array list file containing all the rejected spots. The identifiers of all these spots will be set to ‘empty’ and the description field will notify the reason for the rejection. This file will help the user improve the quality image analysis for its own experiments.


   5 CONCLUSION
TOP
 ABSTRACT
 1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
 4 PRACTICAL USE
 5 CONCLUSION
REFERENCES
 
The goal of Doelan is to help microarray production platforms in managing the quality control steps after the production of batches of slide. The flexible plug-in solution offered by this application enables the software to be fitted to all specific needs. In addition, the use of Doelan is not limited to the quality control of production and can be extended to test the quality of a normal microarray experiment before starting the analysis process. Currently, the Doelan application was implemented to use files from the GenePix image analysis software, but the input file management is done using filters and the creation of new filters for other image analysis software (QuantArray, ScanArray, etc.) could be done very easily.


   Acknowledgments
 
We wish to thank the staff from the ENS transcriptome platform and collaborators for script testing. We thank F. Devaux and C. Jacq for their comments on the manuscript, and H. Roest Crollius for critical review of the paper. This work is partly supported by the French RNG (Genopole National Network).

Conflict of Interest: none declared.

Received on July 21, 2005; revised on September 15, 2005; accepted on September 20, 2005

   REFERENCES
TOP
 ABSTRACT
 1 INTRODUCTION
 2 DOELAN PRINCIPLE AND...
 3 AVAILABLE TESTS
 4 PRACTICAL USE
 5 CONCLUSION
 REFERENCES
 

    Buness, A., et al. (2005) arrayMagic: two-colour cDNA microarray quality control and preprocessing. Bioinformatics, 21, 554–556[Abstract/Free Full Text].

    Hautaniemi, S., et al. (2003) A novel strategy for microarray quality control using Bayesian networks. Bioinformatics, 19, 2031–2038[Abstract/Free Full Text].

    Hessner, M.J., et al. (2004) Utilization of a labeled tracking oligonucleotide for visualization and quality control of spotted 70-mer arrays. BMC Genomics., 5, 12[CrossRef][Medline].

    Model, F., et al. (2002) Statistical process control for large scale microarray experiments. Bioinformatics, 18, S155–S163[Abstract].

    Reimers, M. and Weinstein, J.N. (2005) Quality assessment of microarrays: visualization of spatial artifacts and quantitation of regional biases. BMC Bioinformatics, 1, 166.

    Sauer, U., et al. (2005) Quick and simple: quality control of microarray data. Bioinformatics, 21, 1572–1578[Abstract/Free Full Text].

    Shearstone, J.R., et al. (2002) Nondestructive quality control for microarray production. Biotechniques, 32, 1051–1057[Medline].

    Tran, P.H., et al. (2002) Microarray optimizations: increasing spot accuracy and automated identification of true microarray signals. Nucleic Acids Res., 30, e54[Abstract/Free Full Text].


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This Article
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