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. 2020 Jun 29;11:3264. doi: 10.1038/s41467-020-16958-3

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 1 — a Workflow of DNA data storage. Digital information is first encoded into oligonucleotide (oligo) sequences, resulting in multiple 150-base DNA fragments synthesized using array-based DNA synthesis technology, which are then stored. To read back the stored data, target DNA oligos can be selectively (random-) accessed using polymer chain reaction (PCR), then sequenced via next generation sequencing (NGS), and decoded back to digital information. b The computational model approximates each molecular process in the DNA storage system: it uses a normal distribution for modeling sequence copy numbers from synthesis, a stochastic branching process for PCR, and random sampling for sequencing. The computational model makes predictions for oligo copy distribution to help researchers estimate statistics such as sequence dropout rate.