Advertisement

Machine Vision and Applications

, Volume 17, Issue 5, pp 337–345 | Cite as

A noise-resistant algorithm for grid finding in microarray image analysis

  • Eugene NovikovEmail author
  • Emmanuel Barillot
Original Paper

Abstract

We present an algorithm for automatic spot localization for microarray images with rectangular spot and block packing. As an input, the algorithm requires only the common array design parameters: number of block rows and columns and number of spot rows and columns within each block. It proved to be robust with respect to different types of contamination and can tolerate a high percentage of the missing spots. The validity of the developed algorithm has been tested and confirmed using a large set of images of various designs from different microarray platforms. Comparison with academic and commercial packages has shown that for uncontaminated images our algorithm performs similarly, whereas for certain problematic images it outperforms the other packages.

Keywords

Microarray image analysis Automatic spot localization Grid finding Spot addressing 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Angulo J., Serra J. (2003) Automatic analysis of DNA microarray images using mathematical morphology. Bioinformatics 19, 553–562CrossRefGoogle Scholar
  2. 2.
    Axon Instruments, Inc.: GenePix Pro 5.0. http://www.axon. com, User’s Guide and Tutorial (2003)Google Scholar
  3. 3.
    Buhler, J., Ideker, T., Haynor, D.: Dapple: improved techniques for finding spots on DNA microarrays. UW CSE Technical Report UWTP 2000-08-05 (2000)Google Scholar
  4. 4.
    Galinsky V.L. (2003) Automatic registration of microarray images. I. Rectangular grid. Bioinformatics 19, 1824–1831CrossRefGoogle Scholar
  5. 5.
    Hegde P., Qi R., Abernathy K., Gay C., Dharap S., Gaspard R., Hughes J.E., Snesrud E., Lee N., Quackenbush J. (2000) A concise guide to cDNA microarray analysis. Biotechniques 29, 548–562Google Scholar
  6. 6.
    Herzel H., Beule D., Kielbasa S., Korbel J., Sers C., Malik A., Eickhoff H., Lehrach H., Schuchhardt J. (2001) Extracting information from cDNA arrays. Chaos 11, 98–107zbMATHCrossRefGoogle Scholar
  7. 7.
    Ishkanian A.S., Malloff C.A., Watson S.K., DeLeeuw R.J., Chi B., Coe B.P., Snijders A., Albertson D.G., Pinkel D., Marra M.A., Ling V., MacAulay C., Lam W.L. (2004) A tiling resolution DNA microarray with complete coverage of the human genome. Nat. Genet. 36, 299–303CrossRefGoogle Scholar
  8. 8.
    Jain A.N., Tokuyasu T.A., Snijders A.M., Segraves R., Albertson D.G., Pinkel D. (2002) Fully automated quantification of microarray image data. Genome Res. 12, 325–332CrossRefGoogle Scholar
  9. 9.
    Jung H.Y., Cho H.G. (2002) An automatic block and spot indexing with k-nearest neighbors graph for microarray image analysis. Bioinformatics 18, (Suppl. 2) S141–S151Google Scholar
  10. 10.
    Koada Technology (2004) Koadarray V.2.3.16. http://www.koada.comGoogle Scholar
  11. 11.
    Niles Scientific (2004) SpotReader V.1.1.1.4. http://www.nilesscientific.comGoogle Scholar
  12. 12.
    Pinkel D., Segraves R., Sudar D., Clark S., Poole I., Kowbel D., Collins C., Kuo W.L., Chen C., Zhai Y., Dairkee S.H., Ljung B.M., Gray J.W., Albertson D.G. (1998) High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat. Genet. 20, 207–211CrossRefGoogle Scholar
  13. 13.
    Steinfath M., Wruck W., Seidel H., Lehrach H., Redelof U., O’Brien J. (2001) Automated image analysis for array hybrodization experiments. Bioinformatics 17, 634–641CrossRefGoogle Scholar
  14. 14.
    Yang Y.H., Buckley M.J., Dudoit S., Speed T.P. (2002) Comparison of methods for image analysis on cDNA microarray data. J. Comput. Graph. Stat. 11, 108–136CrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Service BioinformatiqueInstitut CurieParis Cedex 05France

Personalised recommendations