@article{organick2018random,
author = {Organick, Lee and Dumas Ang, Siena and Chen, Yuan-Jyue and Lopez, Randolph and Yekhanin, Sergey and Makarychev, Konstantin and Racz, Miklos Z and Kamath, Govinda and Gopalan, Parikshit and Nguyen, Bichlien and Takahashi, Christopher N and Newman, Sharon and Parker, Hsing-Yeh and Rashtchian, Cyrus and Stewart, Kendall and Gupta, Gagan and Carlson, Robert and Mulligan, John and Carmean, Doug and Seelig, Georg and Ceze, Luis and Strauss, Karin},
title = {Random Access in Large-Scale DNA Data Storage},
year = {2018},
month = {March},
abstract = {Synthetic DNA is durable and can encode digital data with high density, making it an attractive medium for data storage. However, recovering stored data on a large-scale currently requires all the DNA in a pool to be sequenced, even if only a subset of the information needs to be extracted. Here, we encode and store 35 distinct files (over 200 MB of data), in more than 13 million DNA oligonucleotides, and show that we can recover each file individually and with no errors, using a random access approach. We design and validate a large library of primers that enable individual recovery of all files stored within the DNA. We also develop an algorithm that greatly reduces the sequencing read coverage required for error-free decoding by maximizing information from all sequence reads. These advances demonstrate a viable, large-scale system for DNA data storage and retrieval.},
url = {http://approjects.co.za/?big=en-us/research/publication/random-access-in-large-scale-dna-data-storage/},
journal = {Nature Biotechnology},
volume = {36},
number = {3},
}