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Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data


ABSTRACT: Motivation Recently, single-cell DNA sequencing (scDNA-seq) and multi-modal profiling with the addition of cell-surface antibodies (scDAb-seq) have provided key insights into cancer heterogeneity. Scaling these technologies across large patient cohorts, however, is frequently cost and time prohibitive. Multiplexing, in which cells from unique patients and pooled into a single experiment, offers a possible solution. While multiplexing methods are available for scRNAseq, accurate demultiplexing in scDNAseq remains an unmet need. Results Here, we introduce SNACS: Single-Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting. SNACS relies on a combination of patient-level cell-surface identifiers and natural variation in genetic polymorphisms to demultiplex scDNAseq data. We demonstrated the performance of SNACS on a dataset consisting of multi-sample experiments from patients with leukemia where we knew truth from single-sample experiments from the same patients. Relative to demultiplexing methods derived from the scRNAseq literature, SNACS offered superior accuracy. Availability Implementation SNACS is available at https://github.com/olshena/SNACS.

ORGANISM(S): Homo sapiens

PROVIDER: GSE255224 | GEO | 2024/02/09

REPOSITORIES: GEO

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