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Updated: Feb 21, 2026

Identification of Mouse and Human Antibody Repertoires by Next-Generation Sequencing
Published on: March 15, 2019
Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations
Alexander Yermanos1, Victor Greiff1, Nike Julia Krautler2
1Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland.
Motivation:
The evolution of antibody repertoires represents a hallmark feature of adaptive B-cell immunity. Recent advancements in high-throughput sequencing have dramatically increased the resolution to which we can measure the molecular diversity of antibody repertoires, thereby offering for the first time the possibility to capture the antigen-driven evolution of B cells. However, there does not exist a repertoire simulation framework yet that enables the comparison of commonly utilized phylogenetic methods with regard to their accuracy in inferring antibody evolution.
Results:
Here, we developed AbSim, a time-resolved antibody repertoire simulation framework, which we exploited for testing the accuracy of methods for the phylogenetic reconstruction of B-cell lineages and antibody molecular evolution. AbSim enables the (i) simulation of intermediate stages of antibody sequence evolution and (ii) the modeling of immunologically relevant parameters such as duration of repertoire evolution, and the method and frequency of mutations. First, we validated that our repertoire simulation framework recreates replicates topological similarities observed in experimental sequencing data. Second, we leveraged Absim to show that current methods fail to a certain extent to predict the true phylogenetic tree correctly. Finally, we formulated simulation-validated guidelines for antibody evolution, which in the future will enable the development of accurate phylogenetic methods.
Availability And Implementation:
https://cran.r-project.org/web/packages/AbSim/index.html.
Contact:
sai.reddy@ethz.ch.
Supplementary Information:
Supplementary data are available at Bioinformatics online.

