LoosC / systemsseRology

Machine learning tools for the analysis of systems serology data

systemsseRology

About

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").

Installation

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")
install_github("LoosC/systemsseRology", ref = "reboot")
library(systemsseRology)

Selected Papers

systemsseRology has been employed in a number of papers, including:

• Bartsch, Y. C. et. al. (2021). Viral Rebound Kinetics Correlate with Distinct HIV Antibody Features. Mbio, 12(2).

• Herman, J. D. et. al. (2021). Functional Antibodies in COVID-19 Convalescent Plasma. medRxiv.

• Bartsch, Y. C. et. al. (2021). Humoral signatures of protective and pathological SARS-CoV-2 infection in children. Nature medicine, 1-9.

• 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.

• Krystle, K. Q. et. al. (2021). Comorbid illnesses are associated with altered adaptive immune responses to SARS-CoV-2. JCI insight.