This is a pre-copyedited, author-produced version of an article accepted for publication in Bioinformatics following peer review. The version of record Sergio Picart-Armada, Wesley K Thompson, Alfonso Buil, Alexandre Perera-Lluna; diffuStats: an R package to compute diffusion-based scores on biological networks, Bioinformatics, Volume 34, Issue 3, 1 February 2018, Pages 533–534 is available online at: https://doi.org/10.1093/bioinformatics/btx632.

Label propagation and diffusion over biological networks are a common mathematical formalism in computational biology for giving context to molecular entities and prioritising novel candidates in the area of study. There are several choices in conceiving the diffusion process -involving the graph kernel, the score definitions and the presence of a posterior statistical normalisation- which have an impact on the results. This manuscript describes diffuStats, an R package that provides a collection of graph kernels and diffusion scores, as well as a parallel permutation analysis for the normalised scores, that eases the computation of the scores and their benchmarking for an optimal choice.

Peer Reviewed