lionessR: single-sample network reconstruction in R

Kuijjer, M. L.; Quackenbush, J.; Glass, K.

doi:10.1101/582098

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bioRxiv · 10.1101/582098

lionessR: single-sample network reconstruction in R

Kuijjer, M. L.·Quackenbush, J.·Glass, K.

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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 LIONESS was originally made available as a function within the PANDA (Passing Attributes between Networks for Data Assimilation) regulatory network reconstruction framework.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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Kuijjer, M. L., Quackenbush, J., Glass, K.. 2019-03-21. lionessR: single-sample network reconstruction in R. https://doi.org/10.1101/582098

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