ZüKoSt: Seminar on Applied Statistics

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Spring Semester 2012

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23 February 2012
16:15-17:30

Rainer Spang
Universität Regensburg

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ZueKoSt: Seminar on Applied Statistics

Title	Modeling cell perturbation data
Speaker, Affiliation	Rainer Spang, Universität Regensburg
Date, Time	23 February 2012, 16:15-17:30
Location	HG G 19.1
Abstract	Functional genomics has a long tradition of inferring the inner working of a cell through analysis of its response to various perturbations. Observing cellular features after knocking out or silencing a gene reveals which genes are essential for an organism or for a particular pathway. A key obstacle to inferring genetic networks from perturbation screens is that phenotypic profiles generally offer only indirect information on how genes interact. I will discuss a network inference method that we called Nested Effects Models (NEM). It can be used to model the flow of information in cells based on the nested structure of downstream effects of perturbations like RNAi mediated gene knockdowns. Special attention will be given to strategies for controlling network complexity. I will demonstrate the power of our method in the context of modelling disrupted Wnt signalling in colorectal cancers.

Modeling cell perturbation dataread_more

HG G 19.1

* 15 March 2012
16:15-17:30

Sander Greenland
University of California, Los Angeles

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ZueKoSt: Seminar on Applied Statistics

Title	Causal Inference: Much More than Just Statistics (at the University Zurich, Rämistrasse 73)
Speaker, Affiliation	Sander Greenland, University of California, Los Angeles
Date, Time	15 March 2012, 16:15-17:30
Location	RAK E 8
Abstract	There has been an explosion of statistical techniques labeled "causal inference methods," in which the statistical analysis model is at least partly derived from a formal causal model. Discussions of these methods may leave the impression that they solve a unique and general problem of causal inference. That is not the case: Formal causal inference methods thus far focus on idealized special cases in which the only available evidence comprises one study or a set of similar studies, whereas there are usually diverse evidence sources that must be merged to form credible inferences. This reality is addressed by informal "criterion" or "checklist" approaches typified by Bradford Hill's nine causal considerations. Attempts to at least partially formalize causal considerations have as yet had limited contact with formal causal modeling, although those considerations can be formalized and merged with causal modeling to produce predictive theories of causal inference. Nonetheless, the effort required for integrative approaches combined with pressures to claim inferences from single evidence sources remain formidable obstacles to implementation of those approaches,

Causal Inference: Much More than Just Statistics (at the University Zurich, Rämistrasse 73)read_more

RAK E 8

10 May 2012
16:15-17:30

Björn Bornkamp
Technische Universität Dortmund

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ZueKoSt: Seminar on Applied Statistics

Title	Prior distributions for dose-response
Speaker, Affiliation	Björn Bornkamp, Technische Universität Dortmund
Date, Time	10 May 2012, 16:15-17:30
Location	HG G 19.1
Abstract	In this talk I will present a new framework for deriving prior distributions in nonlinear dose-response modelling situations. Determination of the prior in these situations is challenging, as traditional approaches for prior selection in the case of little prior information (such as Jeffreys prior) are not adequate, which lead practitioners to choose prior distributions based on a mix of heuristic considerations and extensive simulations. In addition in pharmaceutical dose-response type trials the data are typically sparse, with a relatively small signal to noise ratio, which means that the prior will have a non- negligible influence on the posterior, which makes the choice of the prior even as more important. The essential idea of our approach is to derive the distribution in a way so that it is uniform in the underlying functional shapes of the nonlinear regression function, giving equal weight to all underlying shapes. We investigate the resulting unference procedure in two pharmaceutical clinical trial examples, and provide practical hints on how to implement the presented priors in Bayesian modelling software.

Prior distributions for dose-responseread_more

HG G 19.1

31 May 2012
16:15-17:30

Bodhisattva Sen
Columbia University New York, University of Cambridge, UK

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ZueKoSt: Seminar on Applied Statistics

Title	Streaming motion in Leo I
Speaker, Affiliation	Bodhisattva Sen, Columbia University New York, University of Cambridge, UK
Date, Time	31 May 2012, 16:15-17:30
Location	HG G 19.1
Abstract	In this talk I will consider an application in Astronomy and illustrate how statistical procedures can be used to answer the important scientific questions. Whether a dwarf spheroidal galaxy is in equilibrium or being tidally disrupted by the Milky Way is an important question for the study of its dark matter content and distribution. This question is investigated using observations from the dwarf spheroidal Leo I. For Leo I, tidal disruption is detected, at least for stars sufficiently far from the centre, but the effect appears to be quite modest.

Streaming motion in Leo Iread_more

HG G 19.1

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Organisers: Peter Bühlmann, Leonhard Held, Markus Kalisch, Hans-Rudolf Künsch, Marloes Maathuis, Martin Mächler, Lukas Meier, Werner Stahel, Sara van de Geer

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