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Bioinformatics
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Bioinformatics
Article . 2018
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Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim)

Authors: Alexander Yermanos; Victor Greiff; Nike Julia Krautler; Ulrike Menzel; Andreas Dounas; Enkelejda Miho; Annette Oxenius; +2 Authors

Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim)

Abstract

Abstract 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 Supplementary information Supplementary data are available at Bioinformatics online.

Country
Switzerland
Keywords

B-Lymphocytes, Genes, Immunoglobulin, High-Throughput Nucleotide Sequencing, Antibodies, Evolution, Molecular, Mice, Animals, Cell Lineage, Computer Simulation, Female, Phylogeny, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
45
Top 10%
Top 10%
Top 10%
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