Hartmann, Alexander K. and Nuel, Grégory (2017) Using triplet ordering preferences for estimating causal effects in the analysis of gene expression data. PLoS one, 12 (1). e0170514. ISSN 1932-6203

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Abstract

Triplet ordering preferences are used to perform Monte Carlo sampling of the posterior causal orderings originating from the analysis of gene-expression experiments involving observation as well as, usually few, interventions, like knock-outs. The performance of this sampling approach is compared to a previously used sampling via pairwise ordering preference as well as to the sampling of the full posterior distribution. For a fair comparison, the latter approach is restricted to twice the numerical effort of the triplet-based approach. This is done for artificially generated causal, i.e., directed acyclic graphs (DAGs) and for actual experimental data taken from the ROSETTA challenge. The sampling using the triplets ordering turns out to be superior to both other approaches.

Item Type:	Article
Additional Information:	Publiziert mit Hilfe des DFG-geförderten Open Access-Publikationsfonds der Carl von Ossietzky Universität Oldenburg.
Uncontrolled Keywords:	Triplet ordering preference, gene-regulation network, Monte Carlo sampling
Subjects:	Science and mathematics > Physics
Divisions:	Faculty of Mathematics and Science > Institute of Physics (IfP)
Date Deposited:	26 Sep 2017 06:12
Last Modified:	01 Dec 2017 10:50
URI:	https://oops.uni-oldenburg.de/id/eprint/3304
URN:	urn:nbn:de:gbv:715-oops-33855
DOI:	10.1371/journal.pone.0170514
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