dc.contributor.author |
Massoni-Badosa, R. |
dc.contributor.author |
Iacono, G. |
dc.contributor.author |
Moutinho, C. |
dc.contributor.author |
Kulis, M. |
dc.contributor.author |
Palau, N. |
dc.contributor.author |
Marchese, D. |
dc.contributor.author |
Rodríguez-Ubreva, Javier |
dc.contributor.author |
Ballestar, E. |
dc.contributor.author |
Rodriguez-Esteban, G. |
dc.contributor.author |
Marsal, S. |
dc.contributor.author |
Aymerich, M. |
dc.contributor.author |
Colomer, D. |
dc.contributor.author |
Campo, E. |
dc.contributor.author |
Julià, A. |
dc.contributor.author |
Martín-Subero, J.I. |
dc.contributor.author |
Heyn, Holger |
dc.contributor.author |
Universitat Autònoma de Barcelona |
dc.date |
2020 |
dc.date.accessioned |
2021-09-15T06:40:56Z |
dc.date.available |
2021-09-15T06:40:56Z |
dc.date.issued |
2021-09-15 |
dc.identifier |
https://ddd.uab.cat/record/236418 |
dc.identifier |
10.1186/s13059-020-02032-0 |
dc.identifier |
oai:ddd.uab.cat:236418 |
dc.identifier |
85084544222 |
dc.identifier |
1474-760Xv21n1p112 |
dc.identifier |
32393363 |
dc.identifier.uri |
http://hdl.handle.net/2072/509415 |
dc.format |
application/pdf |
dc.language |
eng |
dc.publisher |
|
dc.relation |
Instituto de Salud Carlos III CP14-00229 |
dc.relation |
info:eu-repo/grantAgreement/MICINN/SAF2017-89109-P |
dc.relation |
info:eu-repo/grantAgreement/MINECO/IPT-010000-2010-36 |
dc.relation |
Agència de Gestió d'Ajuts Universitaris i de Recerca 2017-SGR-736 |
dc.relation |
Agència de Gestió d'Ajuts Universitaris i de Recerca 2017-SGR-1142 |
dc.relation |
European Commission 210574908 |
dc.relation |
European Commission 810287 |
dc.relation |
Genome biology ; Vol. 21 Núm. 1 (november 2020), p. 112 |
dc.rights |
open access |
dc.rights |
Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original. |
dc.rights |
https://creativecommons.org/licenses/by/4.0/ |
dc.subject |
Single-cell |
dc.subject |
Biobank |
dc.subject |
RNA sequencing |
dc.subject |
Peripheral blood mononuclear cells |
dc.subject |
PBMC |
dc.subject |
Chronic lymphocytic leukemia |
dc.subject |
CLL |
dc.subject |
Sampling |
dc.subject |
Cryopreservation |
dc.subject |
Benchmarking |
dc.title |
Sampling time-dependent artifacts in single-cell genomics studies |
dc.type |
Article |
dc.description.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. |