ArticleResearch square2025
Massively Scalable Single-cell Multiomic Profiling of T Cell Repertoire with REFLEX.
Article in Research square, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
11 authors.
Funding
Abstract
Single-cell profiling of T cell state with immune repertoire is critical for understanding heterogenous T cell phenotypes and responses to antigen, however, existing technologies struggle to generate this information at sufficient throughput to match biological complexity. We present "REFLEX", a novel single-cell method enabling highly scalable, cost-efficient, multiomic profiling with paired-chain TCR sequencing. REFLEX utilizes in-situ reverse transcription with integrated sample multiplexing barcodes in a way that merges seamlessly with the commonly used 10x FLEX platform to allow capture of TCR sequences at unprecedented scale and depth. We profile >2 million cells from CMV-peptide-pulsed T cell expansions, capturing TCR sequences and rich multiomic information from 1.4M T cells, identifying many putative novel CMV reactive clonotypes and illustrating the scale and transformative impact on our understanding of T cell mediated adaptive immunity achievable with REFLEX.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.