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BioinformaticsBMC Cancer
Peer-reviewed journal article

lionessR: single-sample network reconstruction in R

Marieke L. KuijjeriD, Ping‐Han HsiehiD, John F QuackenbushiD, Kimberly GlassiD

Abstract

We recently developed LIONESS (Linear Interpolation to Obtain Network Estimates for Single Samples), a method that can be used together with network reconstruction algorithms to extract networks for individual samples in a population. LIONESS was originally made available as a function within the PANDA (Passing Attributes between Networks for Data Assimilation) regulatory network reconstruction framework. In this application note, we describe lionessR, an R implementation of LIONESS that can be applied to any network reconstruction method in R that outputs a complete, weighted adjacency matrix. As an example, we use lionessR to model single-sample co-expression networks on a bone cancer dataset, and show how lionessR can be used to identify differential co-expression between two groups of patients.\n\nAvailability and implementationThe lionessR open source R package, which includes a vignette of the application, is freely available at https://github.com/mararie/lionessR.\n\nContactmarieke.kuijjer@ncmm.uio.no

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02 /Specification & Classification

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