DNA Microarray Image Analysis - University of Illinois at Urbana ...
DNA Microarray Image Analysis - University of Illinois at Urbana ... DNA Microarray Image Analysis - University of Illinois at Urbana ...
64 MICROARRAY SPOT QUALITY ASSESSMENT
Goals and Objectives of Quality Assessment The main goals of image-based spot quality assessment (or grid screening) are: • to identify grid cells that contain valid spots • to eliminate invalid spots from further analysis • The QA objective is to assess thoroughly a spot quality and associate a quality score with each spot as a reliability coefficient during further processing. • The QA automation objective is to completely eliminate any human interaction, and detect any systematic and unexpected errors. 65
- Page 13 and 14: DNA Microarray Image Analysis • T
- Page 15 and 16: Ideal Microarray Image? 1. Ideal cD
- Page 17 and 18: Microarray Image Technologies • A
- Page 19 and 20: Variations of Grid Geometry • Rot
- Page 21 and 22: Variation of Spot Morphology • Sp
- Page 23 and 24: Examples: Spatially Varying Backgro
- Page 25 and 26: 25 Examples: Spatial Resolution, Li
- Page 27 and 28: IMAGE ANALYSIS: MICROARRAY GRID ALI
- Page 29 and 30: Grid Alignment: Application Domains
- Page 31 and 32: 31 Microarray Grid Alignment: Previ
- Page 33 and 34: Microarray Grid Alignment: Previous
- Page 35 and 36: 35 Grid Alignment Algorithm Overvie
- Page 37 and 38: Image Down-Sampling • Design of r
- Page 39 and 40: Vertical and Horizontal Line Score
- Page 41 and 42: Optional Regularity Enforcement •
- Page 43 and 44: Processing Multiple Grids Line Disc
- Page 45 and 46: Spot Size & Spot Density 45 •Radi
- Page 47 and 48: Missing Spots The fewer the spots i
- Page 49 and 50: Down-sampling •Experimental resul
- Page 51 and 52: Grid Alignment Properties Color Inv
- Page 53 and 54: Multiple Grids: Semi-Automated vs.
- Page 55 and 56: 55 MICROARRAY FOREGROUND SEPARATION
- Page 57 and 58: Foreground Separation Using Spatial
- Page 59 and 60: Foreground Separation Using Intensi
- Page 61 and 62: Foreground Separation From Multi-Ch
- Page 63: Step 1: Separating Spots from Backg
- Page 67 and 68: Quality Assessment: Spot Examples
- Page 69 and 70: Criteria for Assessing Morphologica
- Page 71 and 72: I2K Selecting Valid Pixels - SNR Me
- Page 73 and 74: I2K Selecting Valid Pixels - Topolo
- Page 75 and 76: 75 MICROARRAY DATA QUANTIFICATION A
- Page 77 and 78: Spot Descriptors • Volume of fore
- Page 79 and 80: Visualization of Spot Descriptors S
- Page 81 and 82: Normalization • Normalization usi
- Page 83 and 84: 83 MICROARRAY DATA FUSION, ANALYSIS
- Page 85 and 86: Visualization • Data: 3D cubes,di
- Page 87 and 88: Web-Based Documentation 87 http://a
Goals and Objectives <strong>of</strong> Quality Assessment<br />
The main goals <strong>of</strong> image-based spot quality assessment (or grid<br />
screening) are:<br />
• to identify grid cells th<strong>at</strong> contain valid spots<br />
• to elimin<strong>at</strong>e invalid spots from further analysis<br />
• The QA objective is to assess thoroughly a spot quality and<br />
associ<strong>at</strong>e a quality score with each spot as a reliability<br />
coefficient during further processing.<br />
• The QA autom<strong>at</strong>ion objective is to completely elimin<strong>at</strong>e any<br />
human interaction, and detect any system<strong>at</strong>ic and unexpected<br />
errors.<br />
65
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