systemsseRology is a collection of functions used to analyse multivariate systems serology data. You can learn more about the workflow by looking at vignette("example_analysis").
systemsseRology requires the ropls package:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("ropls")It can then be installed via devtools:
install.packages("devtools")
devtools::install_github("yixiangD/systemsseRology", ref = "main")
# you may be asked to enable force flag if you have already installed systemsseRology, then use the following line instead
# devtools::install_github("yixiangD/systemsseRology", ref = "main", force = TRUE)
library(systemsseRology)- Linear model
- Compute correlation
- Visualize correlation as a chord diagram
systemsseRology has been employed in a number of papers, including:
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Bartsch, Y. C. et. al. (2021). Viral Rebound Kinetics Correlate with Distinct HIV Antibody Features. Mbio, 12(2).
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Herman, J. D. et. al. (2021). Functional Antibodies in COVID-19 Convalescent Plasma. medRxiv.
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Bartsch, Y. C. et. al. (2021). Humoral signatures of protective and pathological SARS-CoV-2 infection in children. Nature medicine, 1-9.
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Gorman, M. J. et. al. (2021). Collaboration between the Fab and Fc contribute to maximal protection against SARS-CoV-2 in nonhuman primates following NVX-CoV2373 subunit vaccine with Matrix-M™ vaccination. bioRxiv.
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Krystle, K. Q. et. al. (2021). Comorbid illnesses are associated with altered adaptive immune responses to SARS-CoV-2. JCI insight.