I’ve been working in R and shell scripting for 13yrs, always looking for an excuse to learn something else. I’ve explored C++, Julia & Rust, but without a real need (I’m not a tool developer), and given my limited time and other commitments, my interest always dies off. How can I make this work?

Specifically: (1) I’m not a big fan of the click-to-insert citation interface — I’d much prefer the LaTeX-style \cite{key}; and (2) when I try to insert a citation in a particular spot, it often jumps and gets grouped with other set of citations in the same paragraph. I use the Chrome extension.

I use Paperpile in Google Docs. It’s reliable, but I’m not so happy about usability.

It gave me a different answer:
The term “Manhattan plot” originated informally within the field of genetics, but there’s no clear record of who first coined it in a formal publication. The name seems to have evolved via community usage rather than being formally introduced by a specific individual

To give it a try, I formatted my recent manuscript with Typst and updated the PDF on medRvix. Looks much better. A minor disappointment is that I need to accommodate big figures with legend on the next page, but “#figure( placement: auto)” does not work well with “set block(breakable: true)”.

I guess my question is how I deal with co-authors who will ask for a Word document of the manuscript

All data are available in a user-friendly interactive Shiny app that you can use to search your favorite genes across conditions (link in the Methods section).

We also investigated splicing dynamics during activation, identifying stimulus-dependent alternative splicing events that affect gene function.

We focused on the SLE-risk variant at the TNFSF4 locus, which lies in a stimulus-dependent open chromatin region, highlighting how studying B cell activation can inform variant function.

We used ATAC-seq to understand chromatin remodeling during activation. We identified key transcription factors and found that stimulus-induced open chromatin regions are enriched for immune-mediated disease heritability.

Using single-cell RNA-seq + CITE-seq, we showed how B cells differentiate under different stimuli, revealing stimulus-dependent fates.

We used bulk RNA-seq to profile B cell transcriptional responses to different stimuli. We uncovered stimulus-dependent gene programs with distinct dynamics and functions.

Thank you, Ana!

We also have bunnies in Boston/Cambridge. Ah, and turkeys.