The future of cell biology, even for small labs, is quantitative and computational. What does this mean and what should it look like?
My group is not there yet, but in this post I’ll describe where we are heading. The graphic below shows my current view of the ideal workflow for my lab.
The graphic is pretty self-explanatory, but to walk you through:
- A lab member sets up a microscopy experiment. We have standardised procedures/protocols in a lab manual and systems are in place so that reagents are catalogued to minimise error.
- Data goes straight from the microscope to the server (and backed-up). Images and metadata are held in a database and object identifiers are used for referencing in electronic lab notebooks (and for auditing).
- Analysis of the data happens with varying degrees of human intervention. The outputs of all analyses are processed automatically. Code for doing these steps in under version control using git (github).
- Post-analysis the processed outputs contain markers for QC and error checking. We can also trace back to the original data and check the analysis. Development of code happens here too, speeding up slow procedures via “software engineering”.
- Figures are generated using scripts which are linked to the original data with an auditable record of any modification to the image.
- Project management, particularly of paper writing is via trello. Writing papers is done using collaborative tools. Everything is synchronised to enable working from any location.
- This is just an overview and some details are missing, e.g. backup of analyses is done locally and via the server.
Just to reiterate, that my team are not at this point yet, but we are reasonably close. We have not yet implemented three of these things properly in my group, but in our latest project (via collaboration) the workflow has worked as described above.
The output is a manuscript! In the future I can see that publication of a paper as a condensed report will give way to making the data, scripts and analysis available, together with a written summary. This workflow is designed to allow this to happen easily, but this is the topic for another post.
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Part of a series on the future of cell biology in quantitative terms.
way to go!
Very curious what is your setup/pipeline 5 years later!
Hi Andrius, I hadn’t looked at this post in a long time… things have changed a bit.
We use Overleaf for collaborative writing and slack for communication, which we weren’t doing at back then. We have still not implemented fully automated analysis on a cluster, but are closer to this since we are now using OMERO and have started to write tools to do image analysis server-side.
We hardly do any analysis these days which is fully manual, and pretty much everything post-analysis, to produce a final figure, is automated.