We present an experimental setup for analysis and prediction on microarray data, specifically designed to identify and correct the impact of the selection bias in high-throughput problems. A number of recently published and overoptimistic studies present feature selection and gene profiling processes incurring in overfitting effects. We outline the selection bias problem and we demonstrate its effect on synthetic and microarray data. Then we introduce and describe a procedure to successfully deals with the problem through extensive resampling and label randomization techniques, employing Support Vector Machines as base classifier and an improved version of the Recursive Feature Elimination algorithm for gene ranking

Control of selection bias in microarray data analysis

Furlanello, Cesare;Serafini, Maria;Merler, Stefano;Jurman, Giuseppe
2003

Abstract

We present an experimental setup for analysis and prediction on microarray data, specifically designed to identify and correct the impact of the selection bias in high-throughput problems. A number of recently published and overoptimistic studies present feature selection and gene profiling processes incurring in overfitting effects. We outline the selection bias problem and we demonstrate its effect on synthetic and microarray data. Then we introduce and describe a procedure to successfully deals with the problem through extensive resampling and label randomization techniques, employing Support Vector Machines as base classifier and an improved version of the Recursive Feature Elimination algorithm for gene ranking
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/2028
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
social impact