ACM transactions on information systems (January) by Association for Computing Machinery

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R We also see that we have succeeded to some degree in focusing our data on tags that are related to cancer growth and development. For instance, brain cancer bulk tissue and normal brain bulk tissue have been separated, even though the were produced by the same laboratory (ri). But some further analysis may be needed since the brain cancer bulk tissue and brain cancer cell line clusters are in two different clusters, which means that there are still significant differences between bulk and cell line tissue in the selected subspace.

A Methodology for Analyzing SAGE Libraries for Cancer Profiling • 47 Fig. 3. Result of OPTICS after error removal, normalization, and missing tag imputation. The first kind of tags does not help in forming clustering structures. It even produces a dilution effect to the true clusters, by disturbing the similarity and dissimilarity of libraries. Thus, these tags are removed and only the discriminating tags are kept for further analysis. ACM Transactions on Information Systems, Vol. 23, No. 1, January 2005.

2001], the KNNimpute method, first selects the k genes that have the most similar expression profiles to the gene having a missing value under some condition; then a weighted average of the k most similar genes that have a value under the same condition is used as an estimate for the missing value. This method is based on the assumptions that errors occur randomly and locally at specific spots on the microarray, and that the gene with the missing value is over- or under-expressed by a similar factor as a small cluster of genes.

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ACM transactions on information systems (January) by Association for Computing Machinery
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