Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis.

ABSTRACT: Single-cell RNA-sequencing (scRNA-Seq) is a compelling approach to directly and simultaneously measure cellular composition and state, which can otherwise only be estimated by applying deconvolution methods to bulk RNA-Seq estimates. However, it has not yet become a widely used tool in population-scale analyses, due to its prohibitively high cost. Here we show that given the same budget, the statistical power of cell-type-specific expression quantitative trait loci (eQTL) mapping can be increased through low-coverage per-cell sequencing of more samples rather than high-coverage sequencing of fewer samples. We use simulations starting from one of the largest available real single-cell RNA-Seq data from 120 individuals to also show that multiple experimental designs with different numbers of

SUBMITTER: Mandric I 

PROVIDER: S-EPMC7599215 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature