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Comparative benchmarking of single-cell transcriptomes and immune repertoires across technologies

King, C.; Iqbal, M.; Shokati, E.; Man Ying Li, C.; Li, R.; Tomita, Y.; Smith, E.; Kawecka, J. A.; Wang, S.; Fenix, K.

2026-04-22 bioinformatics
10.64898/2026.04.20.719117 bioRxiv
Show abstract

Immune receptor profiling enables tracking of individual T or B cell clones across time and tissues, providing insight into immune responses, cancer, and autoimmunity. When combined with single-cell transcriptomics, it links clonotype identity to cellular function, revealing the diversity and dynamics of immune cell populations. This study presents a head-to-head benchmarking comparison of two single-cell immune profiling technologies: droplet-based microfluidics from 10x Genomics (10x) and combinatorial barcoding from Parse Biosciences (Parse). Using matched human samples from PBMCs, the analysis evaluates performance across transcriptomic and T cell immune receptor features to assess data quality, reproducibility, and chain-specific recovery. The findings provide a framework for interpreting single-cell immune profiling platforms and emphasize the importance of accounting for technology-specific biases in bioinformatic analyses.

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