Super excited! Would love to learn where people think we can help the most! But you are right, prioritization will be key.
04.03.2026 23:18
👍 3
🔁 0
💬 2
📌 0
Super excited! Would love to learn where people think we can help the most! But you are right, prioritization will be key.
Absolutely agree!
We look forward to your suggestions!
Looking forward to our Lorentz Center workshop 'Trustworthiness in Proteomics' next week!
We would like to ask for suggestions from the Proteomics Community - please comment under this post! What aspects of FDR control and which particular concerns would be great for us to discuss/brainstorm ?
That's an interesting statement when it was recently shown in multiple publications (e.g. www.nature.com/articles/s41...) that DIA-NN v1.8.1 (superseded by v1.9 shortly after ASMS 2024) does not consistently control FDR. Great to see that more recent versions seem to have improved here.
Tobias finds that DIA-NN 1.9.2 has FDR better under control than 1.8.1 for his dataset, but Spectronaut 19 seems to still be off.
Great presentation! Just FYI: It is a little known fact that the MS1 quantification by CHIMERYS on the MSAID Platform works by deconvoluting isotope envelopes in a similar way as JMod since the inception of the platform a year ago. If you are interested in 9-plex DIA support, feel free to reach out!
Excited to see this published! It is a good step in the process for people to assess their FDR control in proteomics experiments. Great work from @bo-wen.bsky.social and @urikeich.bsky.social in particular who drove this.
Glad to see this published. I hope its message reaches both the communities of practitioners that want to simply use and be able to trust software for the analysis of DIA data, as well as the developers of said software. This is important for the field!
#TeamMassSpec, don't miss my talk about double dipping in DIA data analysis on Tuesday afternoon at #ASMS2025! It's not as savoury as the one below, but will contain a couple of spicy takes. 🙃
Only one week left for #ASMS2025! Join us for our talk on accurate and fast zero-shot peptide spectrum prediction, featuring a deep learning approach that predicts fragment ion intensities—even for peptides with unseen post-translational modifications.
🔗 www.msaid.de/conferences/...
#TeamMassSpec
This is great news for researchers that value data security and privacy when processing proteomics data on-premises and in the cloud! ☁️💻📱
Please see my replies in the two posts linked below for clarification.
bsky.app/profile/mart...
and
bsky.app/profile/mart...
We believe the curves look like this for Spectronaut and DIA-NN because the limited search space of the 2nd pass search obviates proper run-specific FDR control.
CHIMERYS is a spectrum-centric and data acquisition method-agnostic algorithm that deconvolves any MS2 spectrum, regardless of whether it was acquired by DDA, DIA or PRM, thus unifying analysis of bottom-up proteomics data.
@msaid-de.bsky.social @kusterlab.bsky.social www.nature.com/articles/s41...
On platform.msaid.io, we already support semi-tryptic searches. Not quite HLA (yet), but I'd suggest to stay tuned!
Please see my replies in the two posts linked below for clarification.
bsky.app/profile/mart...
and
bsky.app/profile/mart...
We believe the curves look like this for Spectronaut and DIA-NN because the limited search space of the 2nd pass search obviates proper run-specific FDR control.
We believe the ID increase is a function of the sensitivity of the instrument. But ultimately, comparisons like this one are always limited by the fact that one cannot really control for all parameters.
Exactly, because identifications with an eFDR > 1% cannot be called identified at an FDR <= 1%.
You are missing the point. This investigation focuses on the correlation of run-specific precursor-level q-values and run-specific precursor-level entrapment q-values. When reporting a list of IDs, this list has to be controlled at the corresponding FDR, which is what we plotted.
We included the time to generate a spectral library, because spectral libraries are often project-specific and in our experience are rarely generate only once in practice.
Definition of Q.Value according to the DIA-NN README.md
We did not change the plots, because Q.Value is the run-specific precursor q-value according to github.com/vdemichev/Di.... This x-axis is the same for all softwares we compared. You can find your suggested version of Extended Data Fig. 6B below. How do you interpret it?
So glad to see our paper describing #CHIMERYS finally published in @naturemethods.bsky.social ! Check it out!
Join us for our upcoming webinar, where we will introduce the latest features of the MSAID Platform, a web-based, fully automated solution for #proteomics data processing, storage, and analysis—powered by CHIMERYS™ 4.
📅 April 1 | 🕒 17:00
🔗 Register here: events.teams.microsoft.com/event/26ff8b...
I am happy that our first publication showcasing the MSAID Platform is out! Read all about its unique features or try it for free at platform.msaid.io!
That post comes from a time when the Tribrids and the Hybrids were not comparable in terms of NCE.
Chimeric DDA spectra are only 'junk' if you can't deconvolute them properly in a spectrum-centric fashion. If only there was a software capable of doing that... 😅 Check out our preprint on solving this problem: doi.org/10.1101/2024.... DDA, DIA and PRM data analysis with the same algorithm!
We are of course using INFERYS, but yeah. 😅 Our verification is the increase in spectral angle.
Given the data we see, I believe Thermo also spent quite some time on making sure that Astral spectra are similar to the spectra from Hybrids and Tribrids. Maybe @hamishs.bsky.social wants to chip in here.
It might also be related to the actual function that maps CE to NCE. In the past, spectra of the same peptide acquired at NCE 25 on the Tribrids and Hybrids from Thermo looked different. I hear that has since been addressed in an effort to make spectra comparable.
The same problem applies to chimeric spectra in DDA and in fact all chimeric spectra. In CHIMERYS, we resolve that by accounting for charge states during CE calibration.
Ah I see. Thanks for the clarification! 🙂