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NetWeAvers: an R package for integrative biological network analysis with mass spectrometry data

Summary: The discovery of functionally related groups in a set of significantly abundant proteins from a mass spectrometry experiment is an important step in a proteomics analysis pipeline. Here we describe NetWeAvers (Network Weighted Averages) for analyzing groups of regulated proteins in a networ...

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Detalles Bibliográficos
Autores principales: McClellan, Elizabeth A., Moerland, Perry D., van der Spek, Peter J., Stubbs, Andrew P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3810856/
https://www.ncbi.nlm.nih.gov/pubmed/24008417
http://dx.doi.org/10.1093/bioinformatics/btt513
Descripción
Sumario:Summary: The discovery of functionally related groups in a set of significantly abundant proteins from a mass spectrometry experiment is an important step in a proteomics analysis pipeline. Here we describe NetWeAvers (Network Weighted Averages) for analyzing groups of regulated proteins in a network context, e.g. as defined by clusters of protein–protein interactions. NetWeAvers is an R package that provides a novel method for analyzing proteomics data integrated with biological networks. The method includes an algorithm for finding dense clusters of proteins and a permutation algorithm to calculate cluster P-values. Optional steps include summarizing quantified peptide values to single protein values and testing for differential expression, such that the data input can simply be a list of identified and quantified peaks. Availability and implementation: The NetWeAvers package is written in R, is open source and is freely available on CRAN and from netweavers.erasmusmc.nl under the GPL-v2 license. Contact: e.mcclellan@erasmusmc.nl Supplementary information: Supplementary data are available at Bioinformatics online.