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Development, Implementation and Testing of a DNA Microarray Test Suite

Development, Implementation and Testing of a DNA Microarray Test Suite. Ehsanul Haque Mentors: Dr. Cecilie Boysen Dr. Jim Breaux ViaLogy Corp. Outline. Purpose Background Datasets Algorithms Results Conclusion. Purpose. To design tests to assess the results from

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Development, Implementation and Testing of a DNA Microarray Test Suite

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  1. Development, Implementation and Testing of a DNA Microarray Test Suite Ehsanul Haque Mentors: Dr. Cecilie Boysen Dr. Jim Breaux ViaLogy Corp.

  2. Outline • Purpose • Background • Datasets • Algorithms • Results • Conclusion

  3. Purpose To design tests to assess the results from • Different microarray data analysis services • VMAxS, GCOS • Different updates of the same data analysis service • VMAxS_V1, VMAxS_V2, VMAxS_V3, VMAxS_V4 • Different background correction, normalization and summarization methods • VMAxS, PLIER, RMA, dCHIP • Different technologies of microarray data analysis • Affymetrix, ABI, Agilent, GE Healthcare, Illumina

  4. VMAxS Signal Detection via QRI Background Quantum Resonance Interferometry (QRI)– Active Signal Processing VMAxS RA Report (Resonance Amplitude) • Probe level signal data • 11-20 probe per gene • 1 expression value per gene (if from Affymetrix system) DAT or raw image file Only raw data files accepted

  5. From image to gene level data Raw pixel level data Image analysis VMAxS/GCOS Probe level data Background correction Normalization Summarization (PM/MM) VMAxS/MAS5.0/PLIER/RMA Gene level data

  6. Datasets Each Dataset stems from the same raw AffymetrixGeneChip .dat files Method A 3 Replicates * 8 Dilutions 24 Samples Method B 3 Replicates * 8 Dilutions 24 Samples .DAT File Method C 3 Replicates * 8 Dilutions 24 Samples Method D 3 Replicates * 8 Dilutions 24 Samples GeneChip family Human 2A: 54676 genes

  7. Test Suite[R scripting] User File Function CV (Coefficient of Variance) File list & parameters Master Function Function RA (Relative Accuracy) Function DEG (Differential Expressed Gene) Output Other

  8. Algorithm User File Function RA (Rela. Accu.) File list & parameters Using a loop, calls function TABLE.IN to work on the User File list of input datasets Function TABLE.IN Calls other functions, parses different formats of data-sets and provides function RA with the required table. Replaces zero values Calculates Mean & SD Plots Conc. vs. Mean Intensity Creates a list of Median Slope Plots Slope vs. Average of mean intensity Calculates Slope and Ave. of mean intensities Method A Method B Method C Method D Slope 0.497897086864 0.394078146688 0.33660070237 0.211275056257

  9. CV Plot Three Replicates A, B & C

  10. CV Plot With fitted line

  11. 8 DilutionsMean Intensity vs. Concentration

  12. Slope vs. Mean Intensity

  13. Median Slope

  14. Results

  15. Conclusion • Developed and implemented two tests in R • CV & RA (relative accuracy) • Tested 2 X 4 datasets • Different parameters of the same analysis method • Different normalization methods • More tests are needed to draw a better conclusion about the data.

  16. Reference & Acknowledgment References: • Zhijin Wu el al, A Model Based Background Adjustment of Oligonucleotide Expression Arrays, Johns Hopkins University, Dept of Biostatistics Working Papers, 2004, paper 1 • Irizarry et al, Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data, Biostatistics (2003), 4, 2, pp. 249-264 • Cope et al, A Benchmark of Affymetrix GeneChip Expression Measures, Bioinformatics, Vol. 1 no. 1 2003, pp. 1-10 Acknowledgements: • Dr. Cecilie Boysen • Dr. Jim Breaux - Vialogy • Southern California Bioinformatics Summer Institute (SoCalBSI) • National Institute of Health (NIH)

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