In:
Genome Biology, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2020-12)
Kurzfassung:
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.
Materialart:
Online-Ressource
ISSN:
1474-760X
DOI:
10.1186/s13059-020-02032-0
Sprache:
Englisch
Verlag:
Springer Science and Business Media LLC
Publikationsdatum:
2020
ZDB Id:
2040529-7