Recent advances in single cell RNA-seq (scRNA-seq) technology have enabled quantification of underlying heterogeneity within cell populations through identifying gene expression signatures of individual cells to reveal transcriptionally distinct cellular subsets. In addition, scRNA-seq combined with appropriate bioinformatics analyses enable modeling of developmental lineage hierarchies and discovery of rare cell types that would be otherwise masked in bulk RNA-seq data. Comprehensive and systematic analysis of both scRNA-seq and bulk RNA-seq data is critical to the success of the Research Projects (RPs) in this Program. The Bioinformatics and Biostatistics Core (Core B) has been designed to meet this need. The Core B leader (Dr. Stephen Yi) has over 10 years of experience in research and teaching in bioinformatics and biostatistics, especially in gene expression analysis, resulting in more than 30 high-impact publications in the field. Core B services will be used by all three RPs for bioinformatics analysis of scRNA-seq and bulk RNA-seq data on mouse and human (with Core C) TECs, stromal cells, and HAPCs. The Core will also provide biostatistics support for all experiments in the Program. The analytical approaches provided by Core B are essential to the goals of all RPs. The core will provide services in three Tasks for the RPs as follows: Task 1. Data storage and maintenance for all Research Projects (RP) and Cores; Task 2. Perform gene expression analyses on scRNA-seq and bulk RNA-seq data; Task 3. Provide general biostatistics support for data generated from RP 1, 2, 3 and with Core C. The Core B leader will interact frequently with RP and Core C leaders to discuss experimental goals and devise strategies for effective bioinformatics and biostatistical analyses. Successful delivery of Core B services will greatly facilitate the overall program through: (i) serving as a key link of overall program synergy; (ii) mapping transcriptional changes in cells of the human and mouse thymus microenvironment over the perinatal to juvenile transition; and (iii) identifying candidate molecular mechanisms that may play a role in the differential functional potential of cells in the perinatal versus juvenile thymic microenvironment.
