Analysis of Gene Expression Discretization Techniques in Microarray Biclustering

DUSSAUT, JULIETA SOL; GALLO, CRISTIAN A.; CARBALLIDO, JESSICA A.; PONZONI, IGNACIO

Granada

Conferencia; 5th International Work-Conference Bioinformatics and Biomedical Engineering (IWBBIO 2017); 2017

Universidad de Granada

Gene expression biclustering analysis is one of the most commonly used technique to see the interaction between genes under certain experiments or conditions. More specifically in the study of diseases, these methods are used to compare control and affected data in order to identify the involved or relevant genes. In some cases, discretization is needed for these algorithms to work correctly. In this context, the choice of the discretization method is extremely important and has a major impact on the outcome. In this work we analyze several discretization methods for Alzheimer Disease (AD) gene ex-pression data and compare the results of a state-of-art biclustering algorithm after each discretization. The comparison reveals that biclusters obtained from discretized expression values achieve a major coverage and overall en-richment than biclusters generated from real-valued expression data. In particular, a clustering-based discretization method overcomes all competing techniques for the dataset under study, in statistical terms.