Toil enables reproducible, open source, big biomedical data analyses

1. Baker, M. Nature 533, 452–454 (2016). 2. Yachie, N. et al. Nat. Biotechnol. 35, 310–312 (2017). 3. Hadimioglu, B., Stearns, R. & Ellson, R. J. Lab. Autom. 21, 4–18 (2016). 4. ANSI SLAS 1–2004: Footprint dimensions; ANSI SLAS 2–2004: Height dimensions; ANSI SLAS 3–2004: Bottom outside flange dimensions; ANSI SLAS 4–2004: Well positions; (ANSI SLAS, 2004). 5. Mckernan, K. & Gustafson, E. in DNA Sequencing II: Optimizing Preparation and Cleanup (ed. Kieleczawa, J.) 9.128 (Jones and Bartlett Publishers, 2006). 6. Storch, M. et al. BASIC: a new biopart assembly standard for idempotent cloning provides accurate, singletier DNA assembly for synthetic biology. ACS Synth. Biol. 4, 781–787 (2015). open sharing of protocols. With a precise ontology to describe standardized protocols, it may be possible to share methods widely and create community standards. We envisage that in future individual research laboratories, or clusters of colocated laboratories, will have in-house, low-cost automation work cells but will access DNA foundries via the cloud to carry out complex experimental workflows. Technologies enabling this from companies such as Emerald Cloud Lab (S. San Francisco, CA, USA), Synthace (London) and Transcriptic (Menlo Park, CA, USA) could, for example, send experimental designs to foundries and return output data to a researcher. This ‘mixed economy’ should accelerate the development and sharing of standardized protocols and metrology standards and shift a growing proportion of molecular, cellular and synthetic biology into a fully quantitative and reproducible era.