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Grup de recerca en bioestadística i bioinformàtica (GRBIO).
Science Outreach
Clinical trials
Guadalupe Gómez and Erik Cobo
Stay tuned for upcoming seminars and meetings! :
Statistical society links
Investigación del rol de los polimorfismos HLA-DRB1/DQB1 como factores genéticos de susceptibilidad para las formas esporádicas y familiares de la miastenia gravis autoinmune en una población española.
Excelencia María de Maeztu: MDM-2014-0445.
Estrategias para el diagnóstico no invasivo en patología renal: potencial diagnóstico de las microvesículas de la orina en el trasplante renal.
Undergraduate Courses
Graduate Courses
Academic activities
Courses taught by members of GRBIO:
Bioinformatics and “omics” data analysis
Alex Sánchez
One of the main goals of GRBIO is to enhance research of their members by assisting researchers with their statistical analysis. We can provide statistical expertise to the scientific community through consulting, teaching and contract services. Beyond the usual statistical consultancy service that can identify and apply the most appropriate statistical tools to solve a research problem we can extend the analysis service to deal with problems that lie beyond the boundaries of current statistical knowledge maybe due to the complexity of the data or the need for new statistical models. We can also provide training for any staff at any level from beginner to expert and covering any statistical topic from the applied end right through to cutting-edge methodological research.
Multivariate Analysis
Conxita Arenas
Exome Variant Analysis (EVA) Pipeline for NGS Data. Developed in R language, calling external programs for specific tasks. It can be run in parallel using many processors from the same machine, and can be easily extended to run in computer clusters (HPC). Still in its early stages, it's a work in progress that is being used already for production in some research centers.
Statistical tests for label-free LC-MS/MS data by spectral counts, to discover differentially expressed proteins between two biological conditions. Three tests are available: Poisson GLM regression, quasi-likelihood GLM regression, and the negative binomial of the edgeR package.The three models admit blocking factors to control for nuissance variables.To assure a good level of reproducibility a post-test filter is available, where we may set the minimum effect size considered biologicaly relevant, and the minimum expression of the most abundant condition.
Exploratory data analysis to assess the quality of a set of LC-MS/MS experiments, and visualize de influence of the involved factors.