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- Title
Missing value estimation methods for DNA microarrays.
- Authors
Troyanskaya, O; Cantor, M; Sherlock, G; Brown, P; Hastie, T; Tibshirani, R; Botstein, D; Altman, R B
- Abstract
Gene expression microarray experiments can generate data sets with multiple missing expression values. Unfortunately, many algorithms for gene expression analysis require a complete matrix of gene array values as input. For example, methods such as hierarchical clustering and K-means clustering are not robust to missing data, and may lose effectiveness even with a few missing values. Methods for imputing missing data are needed, therefore, to minimize the effect of incomplete data sets on analyses, and to increase the range of data sets to which these algorithms can be applied. In this report, we investigate automated methods for estimating missing data.
- Publication
Bioinformatics (Oxford, England), 2001, Vol 17, Issue 6, p520
- ISSN
1367-4803
- Publication type
Journal Article
- DOI
10.1093/bioinformatics/17.6.520