abtrac is a small companion package to our paper Prevalent and
persistent new-onset autoantibodies in mild to severe COVID-191. The
package demonstrates the clustering approach taken for classification of
new-onset autoantibody trajectories. For details on the rationale and
use case, see the paper.
The clustering method of abtrac is based on the Paritioning Around
Medioids (PAM) algorithm implemented in
cluster::pam()2,
combined with the cosine*euclidean distance metric. Prior to using
abtrac, antibody trajectories are measured using bead arrays and data
are acquired as median fluorescent intensity, in arbitrary units (MFI
[AU]). Using a set point of reference, e.g., seroconversion, MFI are
converted to fold changes (FC). FC are used to cluster trajectories in
abtrac.
Please see the vignette (accessible using browseVignettes("abtrac"))
for an example of running abtrac on the included dataset for antibody
trajectory clustering.
To install the package:
if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("jernbom/abtrac")To load the package:
library(abtrac)Footnotes
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August Jernbom Falk, Lovisa Skoglund, Elisa Pin, Ronald Sjöberg, Hanna Tegel, Sophia Hober, Elham Rostami, Annica Rasmusson, Janet L. Cunningham, Sebastian Havervall, Charlotte Thålin, Anna Månberg, Peter Nilsson. Prevalent and persistent new-onset autoantibodies in mild to severe COVID-19. medRxiv 2024.02.15.24302857; doi: https://doi.org/10.1101/2024.02.15.24302857 ↩
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Maechler M, Rousseeuw P, Struyf A, Hubert M, Hornik K (2023). cluster: Cluster Analysis Basics and Extensions. R package version 2.1.6 ↩