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Cell hashing enable sample multiplexing, multiplet identification and super-loading on droplet-based single cell RNA-sequencing platforms

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE108313
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We reasoned that by using a distinct set of oligo-tagged antibodies against ubiquitously expressed proteins, we could uniquely label multiple populations of cells, multiplex them together, and use the barcoded antibody signal as a fingerprint. We refer to this approach as cellular "hashing", as our set of oligos defines a "look up table" to assign each multiplexed cell to its original sample. We demonstrate application of the technique to combine eight samples and run them simultaneously in a single droplet based scRNA-seq run. We show that cell hashtags allow sample multiplexing, confident multiplet identification and super-loading in the context of a commonly used droplet-based scRNA-seq method to drive down the per-cell cost of large-scale scRNA-seq experiments We chose a set of monoclonal antibodies directed against ubiquitously and highly expressed immune surface markers (CD45, CD98, CD44, and CD11a) and combined these antibodies into eight identical pools (pool A-H), and subsequently conjugated each pool to a distinct hashtag oligonucleotide (henceforth referred to as HTOs). The HTOs contain a unique 10- or 12-bp barcode that could be read out and linked to the cellular transcriptome, through minor modifications to standard scRNA-seq protocols.
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2019-03-27
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