Demultiplexing of single-cell RNA-sequencing data using interindividual variation in gene expression.

ABSTRACT:

Motivation

Pooled designs for single-cell RNA sequencing, where many cells from distinct samples are processed jointly, offer increased throughput and reduced batch variation. This study describes expression-aware demultiplexing (EAD), a computational method that employs differential co-expression patterns between individuals to demultiplex pooled samples without any extra experimental steps.

Results

We use synthetic sample pools and show that the top interindividual differentially co-expressed genes provide a distinct cluster of cells per individual, significantly enriching the regulation of metabolism. Our application of EAD to samples of six isogenic inbred mice demonstrated that controlling genetic and environmental effects can solve interindividual variations related to

SUBMITTER: Nassiri I 

PROVIDER: S-EPMC11193101 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature