Jelle Goeman is professor of biostatistics at Radboud University Medical Center in Nijmegen. He develops statistical methodology for omics data, e.g. methods for gene set testing, prognostic models, and multiple testing. A common theme in his methods is that they allow biological knowledge to be easily and effectively used as part of the analysis.
Title: Flexible multiple testing
Classical methods for multiple testing try to avoid false positive conclusions at all cost. Modern methods based on the False Discovery Rate (FDR), popular in omics data analysis, prefer merely to limit the proportion of false positives among the findings. This is a sensible strategy, as it gives sufficient control over the potential flood of unreliable findings, while simultaneously avoiding too many false negative results. What many users do not realize, however, is that these FDR-based methods allow much less flexibility in the way the results of these methods can be used. For example, simple acts of selection among results or aggregation (e.g. from probe level to gene level) may dramatically increase the proportion of false positives. In this talk I explain why this happens, and propose alternative ways of controlling or estimating the proportion of false positives in such a way that the results allow greater flexibility for the user in later post-processing of the results, e.g. using biological knowledge or bioinformatics tools, while retaining statistically guaranteed properties.
Netherlands Bioinformatics Conference 2014Registration website for Netherlands Bioinformatics Conference 2014
Netherlands Bioinformatics Conference 2014Netherlands Bioinformatics Conference 20140.00EUROnlineOnly2019-01-01T00:00:00Z
Conference Centre De WereltConference Centre De WereltWesthofflaan 2 6741 KH Lunteren Netherlands