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Biological impact of missing-value imputation on downstream analyses of gene expression profiles
2010
Computer applications in the biosciences : CABIOS
Motivation: Microarray experiments frequently produce multiple missing values due to flaws such as dust, scratches, insufficient resolution, or hybridization errors on the chips. Unfortunately, many downstream algorithms require a complete data matrix. The motivation of this work is to determine the impact of missing value imputation on downstream analysis, and whether ranking of imputation methods by imputation accuracy correlates well with the biological impact of the imputation. Methods:
doi:10.1093/bioinformatics/btq613
pmid:21045072
pmcid:PMC3008641
fatcat:fmm3xejlr5c7dm7c6wrfcjcofy