Immune repertoire fingerprinting by principal component analysis reveals shared features in subject groups with common exposures.

ABSTRACT:

Background

Advances in next-generation sequencing (NGS) of antibody repertoires have led to an explosion in B cell receptor sequence data from donors with many different disease states. These data have the potential to detect patterns of immune response across populations. However, to this point it has been difficult to interpret such patterns of immune response between disease states in the absence of functional data. There is a need for a robust method that can be used to distinguish general patterns of immune responses at the antibody repertoire level.

Results

We developed a method for reducing the complexity of antibody repertoire datasets using principal component analysis (PCA) and refer to our method as "repertoire fingerprinting." We reduce the high dimensional space

SUBMITTER: Sevy AM 

PROVIDER: S-EPMC6894320 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature