At least once a year I wish my mentor Dr. Gordon Shepherd were still alive and I could ask him about some obscure neuroanatomy question from the 80s or 90s.

First paper from the lab! Check out our review for Molecular Psychiatry on single-cell studies of brain disease: nature.com/articles/s41380-0…

Transitioning to being a PI in the age of AI Computational biology is in a period of upheaval that is both exhilarating and terrifying. Rapidly, we are approaching a moment of “analytic abundance”, where basically idea you can think of (and several you didn’t) magically appear within minutes of you thinking of them. Of course, the central proximal challenge is the evaluation of the sheer volume results—how do we know they are right when we don’t have the time to check over every line of code? I think it’s very telling that when I talk to AI-pilled faculty, they are exhilerated, but many trainees seem more cautious and far more ambivalent. I think that’s because faculty often have been removed from the details for a long time and probably haven’t checked over a line of code in years. They are used to managing (rather than doing) analysis. Over time, they usually develop a sense for whether things seem right or wrong. In this day and age, this is the skill that you, too, must develop. How do faculty do it? I am guessing every faculty member has their own list of internal sanity checks, but here are a few of mine: * Checksums. I look for things that should add up correctly (percentages add to 100, etc.). If it looks even a little bit off, I ask questions. * Never let go. If something doesn’t make sense, I don’t let go until it does make sense. Never relent! * Explain stray datapoints. Always dig into outliers in the data. How did they come to be? Often, they reveal some hidden assumption or something unexpected about the data. * Do not tolerate warnings. If code gives you a warning, resolve it. Do not continue, do not pass go, until you either understand or eliminate the warning. * Track the number of datapoints. Even a single missing row can be a sign of some fencepost bug. And I’m sure many more that I’m forgetting right now. Basically, it’s a transition from a maker to an interrogator. I also feel it worth reiterating that this is a highly unsetting period of time. I have been fortunate (?) to have 16 years of time to make a transition that people are now being asked to make in months. Again, exhilarating and terrifying, all at once!

Approach sounds very similar to science.org/doi/10.1126/scie…

It’s bittersweet but the scientific review article format is dead. It had a good run. RIP my friend.

What if we could record single-cell RNA levels and videos in the same cells? Our new VISTA-FISH assay links gene expression with neuron firing, lysosome movement, and neuron morphology. VISTA-FISH also detects sgRNAs, enabling live-cell CRISPR screens 🧵 biorxiv.org/content/10.1101/…

I'm really excited to announce that I've been awarded a super prestigious grant from @BrainCanada speaking to my promise as an emerging leader in neuroscience. I'm so grateful to my amazing lab, collaborators, and family. Canada is a great place to be a scientist.