Proceedings of the Korean Operations and Management Science Society Conference (한국경영과학회:학술대회논문집)
- 2006.11a
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- Pages.427-430
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- 2006
Finding significant genes using factor analysis
요인 분석을 이용한 유의한 유전자 추출
Abstract
Clustering for gene expression data without filtering out noise genes may be distorted or derived inappropriate inference. Identifying significant genes and deleting noise before major analysis is necessary fur meaningful discovery from genes expression pattern. We proposed a new method of finding significant genes using factor analysis which is done on transposed data matrix. We construct significance score that is sum of factor loadings for declared significant number of factor, and set threshold through replication. Our proposed method works well for simulated time-course data for finding significant genes even though variance level gets larger.
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