1. IMAGE INFORMATICS SOLUTIONS Extracting Information From Images Array-Pro 4.5 Training, May 2003

2. Array-Pro Analyzer

3. Experiment Model Template concept Experiment definition Default parameters Demo macro: Create Grid Finding Template

4. Experiment Driven

5. Image Acquisition From scanner From files

6. Image Examination Overall image quality On-screen optimization Understanding the intended grid layout Spot shape

7. General Image Analysis Tools Contrast enhancement AOI Navigation and zoom Colorize/color channel Filters Operations Convert/duplicate Surface plot

8. Template Method Development Conceptual framework Rotation Grid location line distance AOI (bounding rectangle) Spot location algorithms Sub-grid definition Cell boundary definition Multiple grid zones Hands on practice

9. Spot location definition –On the first image (creating a template) –On other images Background correction technique Normalization technique Greatest Image Analysis Error Sources

10. Spot ID Wizard

11. Auto Grid/Spot Detection Parameters

12. Advanced Detection

13. Grid Adjustment Manual Save/load/copy/paste Auto align Using Extended auto-align

14. Spot Descriptors ASCII input GAL files URL lookup

15. Replicates within an experiment Adjacent Free assignment By sub-grid By labels

16. How Do You Know Whether Your Data Is Good? Replicates –Is it reproducible within acceptable error? –A tenet of science Standards –No gold standard –Even housekeeping genes change under most experimental conditions –Does it compare favorably to Northern blots?

17. Replicate Handling in Array-Pro

18. Replicates (Cont)

19. Replicate Reporting With so many variables with microarrays, instead of trying to interpret a bad spot image (making assumptions that may not be valid), bad data can be discarded yet still have enough for analysis

20. Measurements Conceptual framework Primary vs. informational measurements Meaning of Net intensity and background

21. Measurements & Statistics Available at four levels –Spots –Replicates –Image groups –Collections of image groups

22. Measurements & Descriptors

23. Spot Measurements

24. Image Group Measurements

25. Quality Metrics User definable Some common ones –Standard deviation of the background pixels –Inertia diameter (indication of spot shape/uniformity) –Spot shift –Number of pixels within threshold

26. Quality Metrics Spot quality metrics User-defined parameters Automatic cell flagging Array quality metrics

27. Optimized Results Only cells failing quality metrics removed; ratio near expected; mean and median ratio close

28. Scatter-plot Display Default method; good but wide variation at low signal; Cy5 signal strength causes distortion Optimized results with much less variance at low signal; excellent linearity

29. View and Labels User feedback definition Color assignment

30. Signal Optimization Background concept Background methods Net intensity definition as found in measurements data table

31. Background Characterization

32. Appropriate Noise Treatment Not as many cells ignored Using statistical parameters: –Mean, Median, Ranked percentile, Trimmed mean Background methods Pre-filtering Net intensity definition as found in measurements data table

33. Using Local Corners About the same

34. Normalization Theory Methods

35. Normalization methods

36. Greatest Sources of Image Acquisition Error Garbage In  Garbage Out –Image analysis can only go so far Dynamic range imbalance of Cy5/Cy3 –Take advantage of 65,536 counts of a 16-bit image Saturation –Pixels truncate at the top end Bleaching –Due to high laser intensity Optics Mechanics

37. Major Factors Influencing Fluorescent Intensity Readings Particulate reflection –Typically 2 to 100 X compared to highest fluorescent signal Temperature pH Oxygen Buffer strength Analyte concentration Time Hybridization efficiency –Kinetics, depletion, etc.

38. CY3/Cy5 Intensity Curves

39. Background/Normalization Correction

40. Data Windows Scatterplot Data table Histogram Cell window Data Graph Information table

41. Cell Groups Standard Custom Derived Automatic cell flagging

42. Cell Groups One can put any group of cells into groups for interpretation

43. Histogram Any measurement or cell group can be displayed; interactive with all other data display windows

44. Cell Window

45. Scatter Plot

46. Data Graph

47. Data Table For information to sort cells and for reporting

48. Statistical Feedback

49. Info Table (Cells)

50. Info Table (Images)

51. Cell Group Information

52. Image Groups Hierarchy Labels

53. Macro Programming Demo macros Macro recorder Sample macros

54. Selling Feature/benefits Demonstration –Overview presentation Demo movies Demo macros –In-depth technical selling to qualified prospects

55. HEADQUARTERS Media Cybernetics, Inc. 8484 Georgia Avenue, Suite 200 Silver Spring, MD 20910 USA Phone: + 1 301 495 3305 Fax: + 1 301 495 5964 Email: info@mediacy.com Web:www.mediacy.com