On the stability and interpretability of prognosis signatures in breast cancer
published: Nov. 8, 2010, recorded: October 2010, views: 1314
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
In this work we wish to answer the questions: (1) how much can we trust the list of genes and the biological functions found in a predictive signature and (2) how do common feature selection methods compare to each other in this regard? We propose a rigorous framework to assess the accuracy, the stability and the interpretability of a feature selection method and compare 8 common feature selection methods as well as ensemble feature selection variants on three breast cancer datasets. Results highlight the very low robustness of most existing methods, including ensemble methods, and raise a warning about the over interpretation of published signatures in terms of genes and biological processes.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !