Label propagation approaches are a widely used procedure in computational biology for giving context to molecular entities using network data. Node labels, which can derive from gene expression, genome-wide association studies, protein domains or metabolomics profiling, are propagated to their neighbours in the network, effectively smoothing the scores through prior annotated knowledge and prioritising novel candidates. The R package diffuStats contains a collection of diffusion kernels and scoring approaches that facilitates their computation and benchmarking.
|Author||Sergio Picart-Armada and Alexandre Perera-Lluna|
|Bioconductor views||GeneExpression GraphAndNetwork Network|
|Maintainer||Sergio Picart-Armada <[email protected]>|
|Package repository||View on GitHub|
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