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public:todag [2015/09/09 09:58]
public:todag [2015/10/01 14:40] (current)
alessandro.romanel@unitn.it [DOWNLOADS]
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-===== ARGENET Algorithm for Reconstruction of GEne NETworks =====+===== TO-DAG - Timed Oncogenetic Directed Acyclic Graphs =====
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 ==== DESCRIPTION ==== ==== DESCRIPTION ====
-Reliable inference of large-scale gene regulatory interactions from experimental data can contribute to a better understanding of cell physiology and pathogenesisARGENET is novel gene network inference tool integrating correlation analysis with variational Bayesian variable selection able to infer directed edges representing putative causal relationships between tens of thousands of genes from non-time-course expression level data.+TO-DAG is an inferential method that deduces from cross-sectional data of genetic alterations in tumor patients the causal dependencies and the waiting times among these genetic eventsFrom matrices with genetic events and patient samples as rows and columns, respectively, TO-DAG generates probabilistic graph model whose nodes represent genetic events and oriented edges between nodes indicate the presence and the direction of a causal dependency between the nodes. A direct acyclic graph, i.e. a graph with no directed cycles, has been specifically chosen as model of putative causal dependencies, as genetic alterations are assumed to be irreversible events. Two parameters define an edge: (i) its probability estimated from the frequency of occurrence of the genetic events represented by the nodes and its conditional probability, and (ii) the waiting time, i.e. the time elapsing from the occurrence of a mutation to the occurrence of another one that is conditionally dependent on it.
 ==== DOWNLOADS ==== ==== DOWNLOADS ====
-== Current version v1 ==+== Source code, example and manual == 
 +  * {{:to-dag-manual.pdf|TO-DAG manual}} 
 +  * {{:to-dag.zip|TO-DAG package}} 
 +== Supplementary materials == 
 +  * {{:graph_figures_graphml.zip|graph_figures_graphml.zip}} 
 +  * {{:graph_figures_xlsx.zip|graph_figures_xlsx.zip}}
-  * {{:argenet.zip|ARGENET package v1.0}} 
-  * {{:argenet_manual.pdf|Manual}}