Statistical methods for TCR-sequencing experiments

The full collection of T-cell receptors within an individual, their TCR repertoire, provides critical insight into and information about the individual's ability to mount any kind of T-cell response. This response can be helpful or harmful, ranging from eradication of an infection or destruction of cancerous cells to an auto-immune attack on the body itself. Technologies have recently been developed that allow for TCR profiling in individual cells providing opportunity to identify rare clonotypes and characterize the TCR repertoire at unprecedented levels of resolution. Unfortunately, much of the potential has yet to be realized as statistical methods to analyze high- throughput TCR-seq data are lacking. This proposal addresses some of the most critical statistical deficiencies that are currently preventing the scientific and clinical communities from turning valuable high-throughput TCR profiling measurements into meaningful results. In particular, we propose statistical methods to ensure that functional TCRs are not lost in pre-processing as well as methods to identify the clonotypes that are most likely to impact disease-relevant immune response. Taken together, successful completion of the project will help to ensure that maximal information is obtained from powerful TCR-seq experiments. Project Number: 1R21AI190872-01 | Fiscal Year: 2025 | NIH Institute/Center: National Institute of Allergy and Infectious Diseases (NIAID) | Principal Investigator: Christina Kendziorski | Institution: UNIVERSITY OF WISCONSIN-MADISON, MADISON, WI | Award Amount: $219,792 | Activity Code: R21 | Study Section: Analytics and Statistics for Population Research Panel A Study Section[ASPA] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R21AI19087201