Institutos Universitarios

Development and implementation of Bayesian methods and design of a user interface for the analysis of contingency tables and expression data

Brief description:

Development and implementation of Bayesian methods for the analysis of contingency tables and expression data. We work with contingency tables for the test of Independence of factors and microarray data for multiple hypothesis testing. Real datasets are analyzed.

Differences between groups are detected with this methods.

A user interfaz is design to develop your own analysis.

A robustness study will be made.



Miguel Ángel Gómez Villegas (Professional Full Professor, Faculty of Mathematics, UCM)
Beatriz González Pérez (Professional Contratado doctor, Faculty of Mathematics, UCM)


External Collaborators:

Luis Sanz San Miguel (Professional Profesor Asociado, Faculty of Mathematics, UCM)
Isabel Salazar Mendoza (Professional Profesor Asociado, Faculty of Veterinary Sciences, UCM)
María Concepción Núñez Pardo de Vera (Professional  Biologist, Instituto de Investigación Sanitaria Hospital Clínico San Carlos)
Juan Padilla Fernández-Vega (Professional Vicerrector de Ordenación Académica y Profesorado, Facultad de Derecho y Economía, Universidad Camilo José Cela)
Óscar Sánchez Becerro (Professional Informatics and PhD student, Faculty of Informatics, UCM)
Gabriel Valverde Castilla (Professional Data Scientist and PhD student, Faculty of Mathematics, UCM)
Óscar de Gregorio Vicente (Professional Project manager and PhD student, Faculty of Mathematics, UCM)


Expected Results:

Differences are found in levels of expression in several genes between the different groups, being notorious for the greater alteration observed in adults. Although more Investigations to evaluate the possible genetic influence that underlies these changes and the specific functional consequences of the differences. It is suggested that a GWAS analysis of the data according to the age of patients could facilitate the identification of new susceptibility and could contribute to reduce the fraction of heritability still unknown, the so-called "missing inheritance". In addition, it could help to find new genetic markers for diagnostic purposes, especially in the group of adults, who have been scarcely represented in the studies of GWAS and commonly show a difficult diagnosis. This studio requires larger samples.