DemuxSNP: supervised demultiplexing single-cell RNA sequencing using cell hashing and SNPs.

ABSTRACT:

Background

Multiplexing single-cell RNA sequencing experiments reduces sequencing cost and facilitates larger-scale studies. However, factors such as cell hashing quality and class size imbalance impact demultiplexing algorithm performance, reducing cost-effectiveness.

Findings

We propose a supervised algorithm, demuxSNP, which leverages both cell hashing and genetic variation between individuals (single-nucletotide polymorphisms [SNPs]). demuxSNP addresses fundamental limitations in demultiplexing methods that use only one data modality. Some cells may be confidently demultiplexed using probabilistic hashing methods. demuxSNP uses these data to infer the genotype of singlet and doublet clusters and predict on cells assigned as negative, uncertain, or doublet using a nearest

SUBMITTER: Lynch MP 

PROVIDER: S-EPMC11604057 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature