Sampling time-dependent artifacts in single-cell genomics studies

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 requir...

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Detalles Bibliográficos
Autores principales: Massoni-Badosa, Ramon, Iacono, Giovanni, Moutinho, Catia, Kulis, Marta, Palau, Núria, Marchese, Domenica, Rodríguez-Ubreva, Javier, Ballestar, Esteban, Rodriguez-Esteban, Gustavo, Marsal, Sara, Aymerich, Marta, Colomer, Dolors, Campo, Elias, Julià, Antonio, Martín-Subero, José Ignacio, Heyn, Holger
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Short Report
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7212672/
https://www.ncbi.nlm.nih.gov/pubmed/32393363
http://dx.doi.org/10.1186/s13059-020-02032-0
Descripción
Sumario: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.

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