Selection bias in working with the top genes in supervised classification of tissue samples

DOI10.1016/j.stamet.2005.09.011zbMath1248.92023OpenAlexW1971104901MaRDI QIDQ713676

D. Kharzeev

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2005.09.011

zbMATH Keywords

cross-validationsupport vector machineerror ratesgene selection

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10)

Related Items (2)

On selection biases with prediction rules formed from gene expression data ⋮ A study of pre-validation

Cites Work

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• Bootstrap methods: another look at the jackknife
• Estimating the Error Rate of a Prediction Rule: Improvement on Cross-Validation
• Analyzing Microarray Gene Expression Data
• Improvements on Cross-Validation: The .632+ Bootstrap Method
• Selection bias in gene extraction on the basis of microarray gene-expression data
• Gene selection for cancer classification using support vector machines

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