ABSTRACT - Biostatistics and Computational Analysis Core (BCAC) The Biostatistics and Computational Analysis Core (BCAC) is a critical supporting core for the proposed project. The BCAC will work closely with all project investigators to meet their bioinformatic, statistical, and data science needs. By making data Findable, Accessible, Interoperable and Reusable (FAIR), the BCAC will maximize the impact and optimize the path to identifying high impact insights on the initial steps of the induction of bNAb precursors, and help to address the knowledge gap whether vaccine adjuvant-induced innate responses impact bNAb precursor development and affinity maturation which are expected to inform the development of new targeted immunomodulatory approaches for HIV vaccine design. The program will generate a suite of longitudinal data with a broad data types, including transcriptomics, single cell (sc) RNA-sequencing, immunome analysis by CyTOF, proteome analysis of soluble immune mediators in plasma, and bacterial presence/abundance in the gut. Such rich data provides unprecedented opportunities to gain insights into innate responses, but also creates analytically challenges to dissect underlying mechanisms of bNAb precursor development, which are intricate with many factors interweaving with each other and jointly impacting bNAb precursor development. The BCAC investigators are recognized experts in biostatistics, data integration across multi-omics, and HIV research, which allows them to address the challenges by providing state-of-the art expertise in a wide range of data science fields. The core will ensure effective data management and data integration. More importantly, the core will develop a suite of innovative approaches to integrate longitudinal immune, microbiome, and molecular signatures to predict the development of bNAb precursors. The sum of the combined results of Projects and Cores provided by the BACA in this Program will be greater than data output that could be achieved by each Program component alone. By integrating the data obtained in Project 1 with microbial signatures identified in Project 2, we expect to make more precise prediction on bNAb precursor development, as defined by the B Cell Core.