AbSim
AbSim simulates time-resolved antibody repertoire evolution to generate realistic B-cell lineage sequences for evaluating and comparing phylogenetic reconstruction methods.
Key Features:
- Time-resolved simulation: Simulates both single lineages using specific sets of V-, D-, and J-genes and full antibody repertoires across evolutionary time.
- Intermediate-stage modeling: Generates intermediate antibody sequence states to represent evolutionary progression over time.
- Immunologically relevant parameters: Incorporates parameters such as duration of repertoire evolution and mutation methods and frequency.
- Topology replication: Produces simulated trees that replicate topological similarities observed in experimental sequencing data.
- Phylogenetic assessment: Enables demonstration and analysis of cases where existing phylogenetic methods fail to recover true evolutionary trees.
Scientific Applications:
- Phylogenetic method benchmarking: Tests the accuracy of phylogenetic reconstruction methods for B-cell lineages and antibody molecular evolution.
- Validation against experimental data: Provides simulated datasets for comparing inferred trees and sequences to experimental sequencing observations.
- Guideline development: Supports formulation of simulation-validated guidelines for interpreting antibody evolution and improving phylogenetic approaches.
Methodology:
Computationally generates antibody sequences and phylogenies calibrated to replicate topological patterns from experimental sequencing data and uses these simulations to validate phylogenetic inference accuracy.
Topics
Details
- License:
- GPL-2.0
- Tool Type:
- library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 6/18/2018
- Last Updated:
- 12/10/2018
Operations
Publications
Yermanos A, Greiff V, Krautler NJ, Menzel U, Dounas A, Miho E, Oxenius A, Stadler T, Reddy ST. Comparison of methods for phylogenetic B-cell lineage inference using time-resolved antibody repertoire simulations (AbSim). Bioinformatics. 2017;33(24):3938-3946. doi:10.1093/bioinformatics/btx533.
Funding: - Swiss National Science Foundation: 31003A_143869, 31003A_170110