By Topic

Sequential diagonal linear discriminant analysis (SeqDLDA) for microarray classification and gene identification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Pique-Regi, R. ; Univ. of Southern California, Los Angeles, CA, USA ; Ortega, A. ; Asgharzadeh, S.

In microarray classification we are faced with a very large number of features and very few training samples. This is a challenge for classical Linear Discriminant Analysis (LDA), since reliable estimates of the covariance matrix cannot be obtained. Alternative techniques based on Diagonal LDA (DLDA) combined with an independent gene selection (filtering) have been proposed. In this paper we propose a novel sequential DLDA (SeqDLDA) technique that combines gene selection and classification. At each iteration, one gene is sequentially added and the linear discriminant (LD) recomputed using the DLDA model (i.e., a diagonal co-variance matrix). Classical DLDA will add the gene with highest t-test score without checking the resulting model. In contrast, SeqDLDA will find the one gene that better improves class separation after recomputing the model measured using a robustified t-test score. We evaluate the new method in several 2-class datasets (Neuroblastoma, Prostate, Leukemia, Colon) using 10-fold cross-validation. For example, for the Neuroblastoma data set, the average misclassification rate of DLDA (16.91%) is significantly reduced to 13.87% using SeqDLDA.

Published in:

Computational Systems Bioinformatics Conference, 2005. Workshops and Poster Abstracts. IEEE

Date of Conference:

8-11 Aug. 2005