Solving the computational challenge of phosphoproteomics with 𝐏𝐡𝐨-𝐓𝐢𝐩: dephosphorylation on-tip identifies the sequences of phosphorylated peptides.

This serves as a basis for predicted spectral libraries, reducing the search space 10x-20x. www.biorxiv.org/content/10.1...

Precisely mapping proteases specificity and predicting cleavage rates - with peptide libraries: doi.org/10.1101/2025.... This is a powerful application that is uniquely enabled by the peptidoform confidence and QuantUMS modules in DIA-NN 2.0.

With 𝗗𝗜𝗔-𝗡𝗡 𝟮.𝟯.𝟬 Preview (Academia-only for now), we showcase the transformative new capabilities that have been developed in the past months. Download: github.com/vdemichev/Di...

We have updated our Slice-PASEF preprint! It's a result of a large collaboration where we highlight its advantages for single cell proteomics. Or any other applications benefiting from sensitivity. For example, major gains for ubiquitinomics:

Time and time again, it's always the same picture. DIA-NN controls FDR correctly as data reliability has been the main goal at DIA-NN's conception back in 2017 and a priority since then.

DIA-NN 2.2.0 is released! The new DIA-NN 2.2.0 Enterprise achieves up to ~1.6x median speedup on 64-cores under Windows (please see benchmark below). Release notes: github.com/vdemichev/Di..., download (Academia): github.com/vdemichev/Di...

Was great to contribute to this fantastic work led by
Patrick Willems @impenslab.bsky.social. With the new proteoform confidence module in DIA-NN, we enabled non-specific digest searches. Here's how it now works for immunopeptidomics!

And there's a clear instruction that Lib.Q.Value filter is mandatory with MBR (link to 1.8.1 user guide github.com/vdemichev/Di..., see screenshot below), and I explained it in detail in Twitter DMs. All this time I've been convinced that you would of course fix this.

How do authors explain this quantification problem with Chimerys?

Following the preprint of this work, I let Martin Frejno know that DIA-NN output was processed in contradiction to its user guide, resulting in nonsense data and plots. Mistakes happen, but puzzling to see these weird plots still in the final version (see below). Well, make your conclusions :)

This is how a QC page per run now looks:

This work shows nicely the advantages of DIA for immunopeptidomics sciencedirect.com/science/arti.... Also, in silico predicted libraries work really well (see Fig. 4). Data were processed with DIA-NN 1.8.2 beta 11, will download and see what 2.0 can do :)

Thanks for sharing raw file! You have high-freq > 20 ppm mass calibration oscillations during the run, solution with DIA-NN is to use --mass-acc-cal 50 - DIA-NN successfully corrects even for that. You see a difference between DIA-NN versions due to different calibration mass tolerances.

Identification numbers and FDR control of Spectronaut 18 vs DIA-NN 1.9 as benchmarked by Jesper Olsen and colleagues (Nature Methods) www.nature.com/articles/s41...

FFPE proteomics workflow on different instruments by Carr lab
www.biorxiv.org/content/10.1...