Based on fast and accurate information collection and understanding of chip,
we are providing a systematic analysis service. |
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Provide the information of Raw data Quality in statistical value and various Plotting. The data that will be used afterwards for analysis is analyzed in most suitable normalized data with the various preprocessing methods (Array-wise centering : Intensity dependent (Global Lowess Normalization), and Block-wise centering (Print-tip Lowess Normalization) )
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Normally it is referred as process of DEG (Differentially Expressed Gene) extraction. It searches the genes that shows revelation differences between the group of analysis objects (For instance, comparison between the control group and experiment group) which contains statistical meanings.
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It is the process called Clustering. It is the process that puts genes or samples together according to similarity of revelation pattern. For the genes we call it Gene Clustering and for the sample we call it Sample Clustering. Gene Clustering is used for the searching of genes function and Sample Clustering is mainly researched for diagnosis of medical field or prediction of prognosis. It conducts the analysis of selected genes with various methods.
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Classification is the sample distinction process. The final aim of the sample distinction process is to get more accurate discriminate results with a small amount of genes. For this, we must select the genes that show the special feature of a group that the user wish to discriminate, classify the samples, and finally, it measures the accuracy of the classification which is most important.
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