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首页> 外文会议>International Conference on Computational Science and Its Applications(ICCSA 2007) pt.3; 20070826-29; Kuala Lumpur(MY) >Effective Quantification of Gene Expression Levels in Microarray Images Using a Spot-Adaptive Compound Clustering-Enhancement-Segmentation Scheme
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Effective Quantification of Gene Expression Levels in Microarray Images Using a Spot-Adaptive Compound Clustering-Enhancement-Segmentation Scheme

机译：使用点自适应化合物聚类-增强-分段方案对芯片图像中基因表达水平进行有效定量

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摘要

A spot-adaptive compound clustering-enhancement-segmentation (CES) scheme was developed for the quantification of gene expression levels in microarray images. The CES-scheme employed 1/griding, for locating spot-regions, 2/Fuzzy C-means clustering, for segmenting spots from background, 3/ background noise estimation and spot's center localization, 4/emphasizing of spot's outline by the CLAHE image enhancement technique, 5/segmentation by the SRG algorithm, using information from step 3, and 6/microarray spot intensity extraction. Extracted intensities by the CES-Scheme were compared against those obtained by the MAGIC TOOL'S SRG. Kullback-Liebler metric's values for the CES-Scheme were on average double than MAGIC TOOL'S, with differences ranging from 1.45bits to 2.77bits in 7 cDNA images. Coefficient-of-Variation results showed significantly higher reproducibility (p<0.001) for the CES-Scheme in quantifying gene expression levels. Processing times for 1024×1024 16-bit microarray images containing 6400 spots were 300 and 487 seconds for the CES-Scheme and MAGIC TOOL respectively.
机译：开发了一种点自适应化合物聚类增强分段（CES）方案，用于量化微阵列图像中的基因表达水平。 CES方案采用1 /网格定位斑点区域，2 /模糊C均值聚类，从背景分割斑点，3 /背景噪声估计和斑点中心定位，4 /通过CLAHE图像增强强调斑点轮廓技术，使用来自步骤3的信息，通过SRG算法进行5 /细分，以及6 /微阵列点强度提取。将通过CES方案提取的强度与通过MAGIC TOOL'S SRG获得的强度进行比较。 CES模式的Kullback-Liebler度量值平均是MAGIC TOOL's的两倍，在7张cDNA图像中，差异在1.45位至2.77位之间。变异系数结果显示，在定量基因表达水平时，CES方案的重现性显着更高（p <0.001）。对于CES-Scheme和MAGIC TOOL，包含6400个斑点的1024×1024 16位微阵列图像的处理时间分别为300秒和487秒。

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