This repository contains the R code necessary to replicate the findings reported in the paper Benedetti et al., "Systematic Evaluation of Normalization Methods for Glycomics Data Based on Performance of Network Inference", Metabolites, 10:7 (2020).
This code was created with R version 4.0.1 and Rstudio version 1.3.959.
Upon sourcing, the script Main.R will automatically download the unprocessed glycomics data used in the paper from the figshare repository and generate the following files into the working directory:
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Barplot_Korcula2.pdf -> corresponding to Figure 3 in the paper
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Barplot_Korcula.pdf -> corresponding to Figure S5 in the paper
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Barplot_Split.pdf -> corresponding to Figure S6 in the paper
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Barplot_Vis.pdf -> corresponding to Figure S7 in the paper
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Barplot_CRC.pdf -> corresponding to Figure 4 in the paper
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AgeAssociation_Korcula2.pdf / AgeAssociation_Korcula.pdf / AgeAssociation_Split.pdf / AgeAssociation_Vis.pdf / AgeAssociation_CRC.pdf -> corresponding to Figure S8 in the paper
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AgeAssociation_Results.xlsx -> corresponding to Table S1 in the paper
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Validation_Summary.pdf / Validation_Summary.xlsx -> corresponding to Table 3 in the paper
Notes:
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The current version of the code performes nboot=100 bootstrapping to compute the confidence intervals of the barplots, while in the paper we used nboot=1000. Increasing the number of bootstrapping will substantially increase the runtime, which for nboot=100 is roughly 9 minutes on a MacBook Pro (macOS version 10.15.1) with a 2.3 GHz Quad-Core Intel Core i5 processor and 16GB of RAM. Results obtained with the default nboot value might slightly differ from the ones reported in the paper due to the difference in bootstrapping samples, but will be qualitatively equivalent.
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One of the glycomics datasets used in the paper is not included in the figshare file (LLS cohort). In order to get access to it, users need to sign a Data Transfer Agreement (see paper for details).