Analytical Biochemistry 2006, 358, 76 - 89

Exploratory data analysis of DNA microarrays by multivariate curve resolution

Joaquim Jaumot, Romà Tauler, Raimundo Gargallo

Abstract

In this work, the application of a Multivariate Curve Resolution procedure based on Alternating Least Squares optimization (MCR-ALS) for the analysis of data from DNA microarrays is proposed. For this purpose, simulated and publicly available experimental data sets have been analyzed. Application of MCR-ALS, a method that operates without the use of any training set, has enabled the resolution of the relevant information about different cancer lines classification using a set of few components; each one of these defined by a sample and a pure gene expression profiles. From resolved sample profiles, a classification of samples according to their origin is proposed. From the resolved pure gene expression profiles, a set of over- or under- expressed genes has been selected, which could be related to the development of cancer diseases. Advantages of the MCR-ALS procedure in relation to other previously proposed, like Principal Component Analysis, are discussed.

Keywords

gene expression data, DNA microarray, Multivariate Curve Resolution, cancer

MCR-ALS resolved sample profiles for the NCI60 data set. (a-g) are the sample profiles for each one of the seven (Ns = 7) components considered. Cyan: breast carcinoma (BR), blue: central nervous system tumor (CNS), orange: colon carcinoma (CO), red: non-small lung cancer (NSLC), yellow: leukemia (LE), black: melanoma (ME), magenta: ovarian carcinoma (OV), violet: prostate cancer (PR), green: renal carcinoma (RE).