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Sampling time-dependent artifacts in single-cell genomics studies

ABSTRACT: Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

ORGANISM(S): Homo sapiens

PROVIDER: GSE132065 | GEO | 2020/04/27

REPOSITORIES: GEO

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