The Ability of Different Imputation Methods to Preserve the Significant Genes and Pathways in Cancer
Rosa Aghdam; Taban Baghfalaki; Pegah Khosravi; Elnaz Saberi Ansari · 2017 · Genomics, Proteomics & Bioinformatics
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Deciphering important genes and pathways from incomplete gene expression data could facilitate a better understanding of cancer. Different imputation methods can be applied to estimate the missing values. In our study, we evaluated various imputation methods for their performance in preserving significant genes and pathways. In the first step, 5% genes are considered in random for two types of ignorable and non-ignorable missingness mechanisms with various missing rates. Next, 10 well-known imputation methods were applied to the complete datasets. The significance analysis of microarrays (SAM)
Abstract by Rosa Aghdam; Taban Baghfalaki; Pegah Khosravi; Elnaz Saberi Ansari, Genomics, Proteomics & Bioinformatics (2017) — licensed CC BY 4.0.
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Metadata source: DOAJ · DOI 10.1016/j.gpb.2017.08.003
