Sampling artifacts in single-cell genomics cohort studies

Ramon Massoni-Badosa; Giovanni Lo Iacono; Cátia Moutinho; Marta Kulis; Núria Palau; Doménica Marchese; Javier Rodríguez‐Ubreva; Esteban Ballestar; Gustavo Rodríguez-Esteban; Sara Marsal; Marta Aymerich; Dolors Colomer; Elı́as Campo; Antonio Julià; José Ignacio Martín-Subero; Holger Heyn

doi:10.1101/2020.01.15.897066

GenomicsbioRxivJan 15, 2020

Preprint

Sampling artifacts in single-cell genomics cohort studies

Ramon Massoni-Badosa iD, Giovanni Lo Iacono iD, Cátia Moutinho iD, Marta Kulis iD, Núria Palau, Doménica Marchese iD, Javier Rodríguez‐Ubreva iD, Esteban Ballestar iD, Gustavo Rodríguez-Esteban iD, Sara Marsal iD, Marta Aymerich iD, Dolors Colomer iD, Elı́as Campo iD, Antonio Julià iD, José Ignacio Martín-Subero iD, Holger Heyn iD

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.

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