A new research article was published in ImmunoInformatics
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Where single-cell transcriptomics fails T cells: The misuse of unsupervised clustering for T-cell annotation
sciencedirect.com/science/ar…@chevaliersf
Very proud to have been a jury member at the newly revived @RSGBelgium hackathon! Exciting to see so many people giving their best efforts tackling challenging #bioinformatics problems. @iscbsc
The AIRR Diagnostics WG commentary is now available, wherein our members discuss both the challenges of current #AIRR-based #diagnostics, as well as the future directions that we see the field going into! #Immunology#tcr#bcr
#ATCR25 acceptance notifications just went out! We had 76 abstracts of very high quality, but could only accept 8! for short talks (so 10%). Huge thanks to our review committee for making though decisions. Really excited where the #TCR field is going based on the abstracts I saw!
#Abstract submission deadline for #ATCR2025 is this Friday!
We are again very grateful to have such a strong lineup of #Tcell receptor experts joining us in Antwerp. Currently at 80% capacity so do not wait to register.
uantwerpen.be/atcr2025
Very excited that today @FWOVlaanderen granted my two #immunology#AI research projects:
* One on modelling #Tcells after #vaccination with my good friend Benson Ogunjimi
* One on mapping the human #MHC presentation space with the ever talented Wout Bittremieux
The annual gathering of #Antwerp bioinformatics at the @biominaBE Research Day, kicked off by @KrisLaukens . Always amazing to see the varied #bioinformatics applications, from fish genomics to clinical biomarkers!
A new paper, led by @kerry_mullan from Pieter Meysman’s (@chevaliersf) group, advocates for a TCR-centric approach to analyzing scRNA data from T cells. One highlight is the identification of melanoma- and colitis-specific TCR clusters. | @ScienceAdvancesdoi.org/10.1126/sciadv.adr31…
Massive effort by @kerry_mullan to recontextualize
data is now out in Science Advances! We developed a new system STEGO to do a TCR-first analysis, and reanalyzed 12 studies and more than 500 000 individual T-cells. Supported by @cziscience@ELIXIRnodeBEdoi.org/10.1126/sciadv.adr31…
We have kept building on the data set, and a larger version including annotations is available on Zenodo as a T-cell atlas.
zenodo.org/records/12606320
This is the first time we have been forced to include an 'Extended Discussion' section in the supplementals because there was just so much that we found. Rather than splitting it over a dozen smaller papers, we opted to put everything into one for a complete story.
Taking all the data together, we also find interesting patterns that occur across studies and individuals. One of them is very clearly MAIT cells, which appear nearly everywhere.
But we also find two other TCRalpha patterns across many individuals that we weren't able to explain. They are clearly enriched compared to the background, but functionally look like any other T-cell (or a mix).