Exploratory data analysis of DNA microarrays by multivariate curve resolution.
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 of these defined by a sample and a pure gene expression profile. 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 underexpressed genes that could be related to the development of cancer diseases has been selected. Advantages of the MCR-ALS procedure in relation to other previously proposed procedures such as principal component analysis are discussed.
Jaumot
Joaquim
J
Department of Analytical Chemistry, Universitat de Barcelona, Diagonal 647, E-08028 Barcelona, Spain.
Tauler
Romà
R
Gargallo
Raimundo
R
D000208:Acute Disease; D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D007951:Leukemia, Myeloid / Q000378:metabolism; D009369:Neoplasms / Q000737:chemistry; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000378:metabolism; D012334:RNA, Neoplasm / Q000032:analysis
D012334:RNA, Neoplasm