TY - JOUR T1 - The influence of the phylogenetic inference pipeline on murine antibody repertoire sequencing data following viral infection JF - bioRxiv DO - 10.1101/2020.03.20.000521 SP - 2020.03.20.000521 AU - Alexander Yermanos AU - Victor Greiff AU - Tanja Stadler AU - Annette Oxenius AU - Sai T. Reddy Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/03/22/2020.03.20.000521.abstract N2 - Understanding B cell evolution following vaccination or infection is crucial for instructing targeted immunotherapies when searching for potential therapeutic or virus-neutralizing antibodies. Antibody phylogenetics holds the potential to quantify both clonal selection and somatic hypermutation, two key players shaping B cell evolution. A wide range of bioinformatic pipelines and phylogenetic inference methods have been utilized on antibody repertoire sequencing datasets to delineate B cell evolution. Although the majority of B cell repertoire studies incorporate some aspect of antibody evolution, how the chosen computational methods affect the results is largely ignored. Therefore, we performed an extensive computational analysis on time-resolved antibody repertoire sequencing data to better characterize how commonly employed bioinformatic practices influence conclusions regarding antibody selection and evolution. Our findings reveal that different combinations of clonal lineage assignment strategies, phylogenetic inference methods, and biological sampling affect the inferred size, mutation rates, and topologies of B cell lineages in response to virus infection. ER -