Current demand for understanding the b ehavior of groups of related genes, combined with the greateravailability of data, has led to an increased focus on statistical methods in gene set analysis. In thispaper, we aim to perform a critical appraisal of the methodology based on graphical models developedin Massa et al. (2010) that uses pathway signaling networks as a starting point to develop statisticallysound procedures for gene set analysis. We pay attention to the potential of the methodology withrespect to the organizational aspects of dealing with such complex but highly informative startingstructures, that is pathways. We focus on three themes: the translation of a biological pathway into agraph suitable for modeling, the role of shrinkage when more genes than samples are obtained, theevaluation of respondence of the statistical models to the biological expectations. To study the impactof shrinkage, two simulation studies will be run. To evaluate the biological expectation we will usedata from a network with known behavior that offer the possibility of carrying out a realistic check ofrespondence of the model to changes in the experimental conditions.

Graphical modelling for gene set analysis: a critical appraisal

M. Chiogna;
2015

Abstract

Current demand for understanding the b ehavior of groups of related genes, combined with the greateravailability of data, has led to an increased focus on statistical methods in gene set analysis. In thispaper, we aim to perform a critical appraisal of the methodology based on graphical models developedin Massa et al. (2010) that uses pathway signaling networks as a starting point to develop statisticallysound procedures for gene set analysis. We pay attention to the potential of the methodology withrespect to the organizational aspects of dealing with such complex but highly informative startingstructures, that is pathways. We focus on three themes: the translation of a biological pathway into agraph suitable for modeling, the role of shrinkage when more genes than samples are obtained, theevaluation of respondence of the statistical models to the biological expectations. To study the impactof shrinkage, two simulation studies will be run. To evaluate the biological expectation we will usedata from a network with known behavior that offer the possibility of carrying out a realistic check ofrespondence of the model to changes in the experimental conditions.
2015
V. Djordjilovic; M. Chiogna; S. Massa; C. Romualdi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/646504
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