biostudies-literatureLi MNCI NIH HHSThe Hope Foundationbtae431https://www.ebi.ac.uk/biostudies/studies/S-EPMC11246167biostudies-literatureUnknown40(7)<h4>Motivation</h4>T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed.<h4>Results</h4>In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conductBioinformatics (Oxford, England)A multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data.PMC11246167U10 CA180819U10CA180819Hua XZhao NLi SWu MCLi MfalseA multi-bin rarefying method for evaluating alpha diversities in TCR sequencing data.<h4>Motivation</h4>T cell receptors (TCRs) constitute a major component of our adaptive immune system, governing the recognition and response to internal and external antigens. Studying the TCR diversity via sequencing technology is critical for a deeper understanding of immune dynamics. However, library sizes differ substantially across samples, hindering the accurate estimation/comparisons of alpha diversities. To address this, researchers frequently use an overall rarefying approach in which all samples are sub-sampled to an even depth. Despite its pervasive application, its efficacy has never been rigorously assessed.<h4>Results</h4>In this paper, we develop an innovative "multi-bin" rarefying approach that partitions samples into multiple bins according to their library sizes, conduct2024-01-01T00:00:00Z2024 Jul2026-06-03T05:34:01.65Z2026-04-24T03:14:33.72ZS-EPMC112461673895017510.1093/bioinformatics/btae431