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Feature extraction and normalization algorithms for high-density oligonucleotidegene expression array data
Feature extraction and normalization algorithms for high-density oligonucleotidegene expression array data
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机译:高密度寡核苷酸基因表达阵列数据的特征提取和归一化算法
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摘要
A characteristic intensity of a feature in image data generated by scanning a microarray probe is determined. A set of pixels of the image data that nominally represent the feature is identified. The pixels each have an value (such as an intensity value) associated therewith. For each of a plurality of subsets of the set of pixels, a variation statistic value is determined that corresponds to a variation in the values associated with the pixels of that subset. One of the subsets of pixels is chosen based on the determined variation statistic values. A method is also described to relate a first expression array of probes to a second expression array of probes. A subset of the probe for the arrays is determined based on a comparison of the ordering of the subset of the probes of the second array, according to a particular characteristic of the probes, to the ordering of corresponding probes in the first array according to the particular characteristic of the probes. A relationship of the second expression array to the first expression array is determined based on the subset of probes of the second expression array to the corresponding probes of the first array.
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