Pinto F R, Cowart L Ashley, Hannun Yusuf A, Rohrer B, Almeida J S
Biomathematics Group, Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa 2781-901 Oeiras, Portugal.
Bioinformatics. 2005 Apr 1;21(7):1037-45. doi: 10.1093/bioinformatics/bti074. Epub 2004 Oct 27.
Integrated analysis of expression data and gene ontology annotations is a prime example of biological data that need co-explanatory interpretation. This particular application is used to validate a new method for integrated analysis of varied biological information.
The proposed method consists of determining local correlation coefficients and the corresponding P-values calculated per biological entity. This measure considers the combined intensity and significance of the agreement or disagreement, between two data sources about the same biological entity. The method is applied to the integrated analysis of gene expression and annotation of two gene sets, one from yeast and other from mouse. The potential of the method to generate accurate mechanistic hypothesis is also demonstrated. Specially, negative correlation results pose a new kind of biological hypothesis. Method performance was compared with annotation enrichment methods, and optimal conditions for the superiority of local correlation results are discussed.