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Sampling time-dependent artifacts in single-cell genomics studies

Ramon Massoni-Badosa, Giovanni 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 I. Martín‐Subero, Holger Heyn

2020Genome biology96 citationsDOIOpen Access PDF

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.

Topics & Concepts

BiologyGenomicsGenome BiologyHuman geneticsComputational biologyComputational genomicsSampling (signal processing)Evolutionary biologyFunctional genomicsGeneticsGenomeComputer scienceGeneComputer visionFilter (signal processing)Single-cell and spatial transcriptomicsCell Image Analysis TechniquesAdvanced Biosensing Techniques and Applications
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