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Improved processing of microarray data using image reconstruction techniques

By P. O'Neill, George D. Magoulas and X. Liu


Spotted cDNA microarray data analysis suffers from various problems such as noise from a variety of sources, missing data, inconsistency, and, of course, the presence of outliers. This paper introduces a new method that dramatically reduces the noise when processing the original image data. The proposed approach recreates the microarray slide image, as it would have been with all the genes removed. By subtracting this background recreation from the original, the gene ratios can be calculated with more precision and less influence from outliers and other artifacts that would normally make the analysis of this data more difficult. The new technique is also beneficial, as it does not rely on the accurate fitting of a region to each gene, with its only requirement being an approximate coordinate. In experiments conducted, the new method was tested against one of the mainstream methods of processing spotted microarray images. Our method is shown to produce much less variation in gene measurements. This evidence is supported by clustering results that show a marked improvement in accuracy

Topics: csis
Publisher: IEEE Computer Society
Year: 2003
OAI identifier:

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  1. Axon Instruments Inc.. GenePix Pro Array analysis software.
  2. (1998). Cluster analysis and display of genome-wide expression patterns,” doi
  3. (1987). Clustering by means of medoids,”
  4. (2002). Comparison of methods for image analysis on cDNA microarray data,” doi
  5. (2001). Computational analysis of microarray data,” doi
  6. (2000). Genomic expression programs in the response of yeast cells to environmental changes,” doi
  7. (2000). Genomic expression programs inthe responseofyeastcells toenvironmentalchanges,”Mol.Biol.Cell, doi
  8. (1963). Hierarchical grouping to optimize an objective function,” doi
  9. Human Genome Project Mapping Resource Centre. Human gen1 clone setarray.[Online]Available:
  10. (2002). Improved background correction for spotted doi
  11. (2001). Lucidea Microarray ScoreCard: An integrated analysis tool for microarray experiments. Life Sci. News [Online] Available:
  12. (2000). On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data,” doi
  13. (1997). Practical Statistics for Medical Research. doi
  14. Project Mapping Resource Centre. Human gen1 clone set array.
  15. QuantArray analysis software.
  16. (1997). Ratio-based decisions and the quantitative analysis of cDNA microarray images,” doi
  17. (1994). Seeded region growing,” doi
  18. (1999). Texture synthesis by nonparametric sampling,” in doi
  19. (1999). The chipping forcast I. Nature Genetics Suppl. [Online] Available:
  20. (2002). The chipping forcast II. Nature Genetics Suppl. [Online] Available:
  21. (2002). Tsukiyama,“Improved background correction for spotted doi

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