source: proteomics, 2003, vol.3, pp.392-401 authors: paul cutler, geoffrey heald, ian r

16
1 A novel approach to spot detection for two-dimensional gel electrophoresis images using pixel value collection Source: Proteomics, 2003, vol.3, pp.39 2-401 Authors: Paul Cutler, Geoffrey Heald, I an R. White and Jason Ruan Speaker: Shu-Fen Chiou ( 邱邱邱 ) Date: 2005/03/18

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A novel approach to spot detection for two-dimensional gel electrophoresis images using pixel value collection. Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R. White and Jason Ruan Speaker: Shu-Fen Chiou ( 邱淑芬 ) Date: 2005/03/18. - PowerPoint PPT Presentation

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Page 1: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

1

A novel approach to spot detection for two-dimensional gel electrophoresis images using pixel value collection

Source: Proteomics, 2003, vol.3, pp.392-401

Authors: Paul Cutler, Geoffrey Heald, Ian R.

White and Jason Ruan

Speaker: Shu-Fen Chiou (邱淑芬 )

Date: 2005/03/18

Page 2: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

2

Outline

Introduction Proposed Method Experimental results Conclusions Comment

Page 3: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

3

Introduction

A common goal of proteomic analysis:Quantitation and identification of proteins which are

differentially expressed under defined physiological

conditions. 2D-gel is a proteomic technology.

Page 4: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

4

Introduction

Drawbacks of the available methods: Noise and artefacts Need extensive parameter setting Take much time Operator subjectivity

A new method using a segmentation method involving pixel value collection via serial analysis of the image through its range of density levels.

Page 5: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

5

Proposed method

1616 2d gel image

244 239 233 230 232 236 241 240 242 243 243 243 244 246 244 244

234 218 201 185 190 208 230 237 240 241 242 245 244 244 244 242

228 201 176 157 161 186 221 234 240 242 242 244 244 244 242 243

224 189 157 132 141 174 214 229 237 242 240 242 244 244 243 243

233 212 188 168 177 203 228 235 239 240 239 241 242 243 244 244

239 227 213 202 208 221 234 238 239 237 236 239 241 243 244 243

242 238 236 235 235 236 238 238 232 217 209 212 223 235 243 243

231 241 240 239 239 239 237 234 213 179 162 166 190 217 239 242

229 239 240 240 240 238 233 222 175 123 105 109 135 182 227 239

239 238 240 239 241 240 229 206 132 75 61 67 87 146 214 234

239 238 239 239 241 241 229 200 120 67 56 61 79 139 213 234

239 239 237 238 240 241 231 208 135 80 67 73 97 157 221 236

241 240 238 240 241 241 235 222 174 124 109 118 148 193 231 240

240 240 240 240 241 241 238 228 194 157 144 155 180 212 235 239

240 240 239 240 243 243 239 233 217 200 196 204 217 231 239 240

236 235 238 239 241 242 240 237 229 223 221 227 235 237 236 234

Smallest pixel value:246

Highest pixel value:56

Limits:

•Size (maxSize, minSize)

•Shape (ellipse or circle)

Page 6: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Proposed method0

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1 9 17 25 33 41 49 57 65 73 81 89 97 105113121129137 145153161169177185193201209217225 233241249High

Low

Range:20

675661The first range:56~76

Threshold 1: (56+61+67)/3=61

105109

The second range:105~125Threshold 2: (105+109)/2=107

Page 7: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Proposed method

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75 61 67 87146

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67 56 61 79139

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80 67 73 97157

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Threshold 1:61

Find the pixel <= threshold 1

1

1 1

minSize:12

maxSize:28Spot 1: (10,9), (10,10), (11,10)

Page 8: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Proposed method

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228

201

176

157

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186

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189

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141

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229

206

132

75 61 67 87146

214

234

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241

229

200

120

67 56 61 79139

213

234

239

239

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241

231

208

135

80 67 73 97157

221

236

241

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240

241

241

235

222

174

124

109

118

148

193

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155

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Threshold 2:107

Find the pixel <= threshold 2

1

1 1 1

1 1

1 1 1 1

minSize:12

maxSize:28Spot 1: (10,9), (10,10), (11,10), (9,9), …

Page 9: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Experimental results

Page 10: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

10

Experimental results

Page 11: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

11

Experimental results

Page 12: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

12

Experimental results

Page 13: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Experimental results

Page 14: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Compare with edge detection

Edge detection Proposed method

Page 15: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Conclusions

The method can be automated and hence reduce operator subjectivity.

The method can detect a large dynamic range of spot intensities and areas, and has the potential to detect and resolve merged spots.

Page 16: Source: Proteomics, 2003, vol.3, pp.392-401 Authors: Paul Cutler, Geoffrey Heald, Ian R

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Comment

Find the spots using the pixel value collection