Simple integrative preprocessing preserves what is shared in data sources.
BACKGROUND
Bioinformatics data analysis toolbox needs general-purpose, fast and easily interpretable preprocessing tools that perform data integration during exploratory data analysis. Our focus is on vector-valued data sources, each consisting of measurements of the same entity but on different variables, and on tasks where source-specific variation is considered noisy or not interesting. Principal components analysis of all sources combined together is an obvious choice if it is not important to distinguish between data source-specific and shared variation. Canonical Correlation Analysis (CCA) focuses on mutual dependencies and discards source-specific "noise" but it produces a separate set of components for each source.


RESULTS
It turns out that components given by CCA can be combined easily to produce a linear and hence fast and easily interpretable feature extraction method. The method fuses together several sources, such that the properties they share are preserved. Source-specific variation is discarded as uninteresting. We give the details and implement them in a software tool. The method is demonstrated on gene expression measurements in three case studies: classification of cell cycle regulated genes in yeast, identification of differentially expressed genes in leukemia, and defining stress response in yeast. The software package is available at http://www.cis.hut.fi/projects/mi/software/drCCA/.


CONCLUSIONS
We introduced a method for the task of data fusion for exploratory data analysis, when statistical dependencies between the sources and not within a source are interesting. The method uses canonical correlation analysis in a new way for dimensionality reduction, and inherits its good properties of being simple, fast, and easily interpretable as a linear projection.
Tripathi
Abhishek
A
Department of Computer Science, P,O, Box 68, FI-00014, University of Helsinki, Finland. abhishek@cs.helsinki.fi
Klami
Arto
A
Kaski
Samuel
S
D003198:Computer Simulation; D003628:Database Management Systems; D016208:Databases, Factual; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008954:Models, Biological; D018511:Systems Integration