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Published on: November 17, 2019
NetWeAvers: an R package for integrative biological network analysis with mass spectrometry data
Elizabeth A McClellan1, Perry D Moerland, Peter J van der Spek
1Department of Bioinformatics, Erasmus University Medical Center, Dr. Molewaterplein 50, 3015GE Rotterdam, The Netherlands, Department of Mathematics and Computer Science, Metropolitan State University of Denver, Colorado, USA, Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Bioinformatics Laboratory, Academic Medical Center, University of Amsterdam, Meibergdreef 9, Amsterdam, 1105AZ, The Netherlands, Netherlands Proteomics Centre, H.R. Kruytgebouw, Padualaan 8, 3584CH Utrecht, The Netherlands and Netherlands Bioinformatics Centre, Geert Grooteplein 28, 6525GA Nijmegen, The Netherlands.
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
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