@c_vanderaa

No longer on Twitter, we can keep in touch here: https://xitter.cf/t.co/uVCvMxmBcO

Joined January 2020
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Our new preprint is available on biorXiv: doi.org/10.1101/2023.12.14.5… !🥳 We present scplainer, a principled computational approach to streamline and standardise #MassSpec #SingleCell #proteomics data analysis. Here's a 🧵 with our key messages.
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scplainer will be (very) soon available in scp so that you can try it yourself. Need data? All data used in this work were retrieved using our scpdata package! github.com/UCLouvain-CBIO/sc… github.com/UCLouvain-CBIO/sc…
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As always, many thanks to my promoter Laurent Gatto for his supervision. I also warmly thank Manon Martin and Bernadette Govaerts for their guidance on the APCA+ framework.
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Christophe Vanderaa retweeted
Dario Righelli@drighelli14 Sep 2023
Our last work on #SingleCellMultiModal data collection is finally out! 🎉 It has been a long journey 🚀, but it taught me a lot! 🥸 Thanks to all the co-authors (in the comments), I really enjoyed working with all of you! 🤩 doi.org/10.1371/journal.pcbi… (1/5)

Curated single cell multimodal landmark datasets for R/Bioconductor

Author summary Experimental data packages that provide landmark datasets have historically played an important role in the development of new statistical methods in Bioconductor by lowering the...

journals.plos.org
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And I forgot to mention that we performed data exploration and illustration using our @Bioconductor tools: scp and scpdata 😅
Christophe Vanderaa@c_vanderaa14 Apr 2023
So glad to share with you our new preprint: arxiv.org/abs/2304.06654 🥳 In this perspective, we discuss how to deal with missing values in #MassSpec #SingleCell #proteomics. Here's a 🧵 with our key messages.

Revisiting the thorny issue of missing values in single-cell proteomics

Missing values are a notable challenge when analysing mass spectrometry-based proteomics data. While the field is still actively debating on the best practices, the challenge increased with the...

arxiv.org
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#Reproducible data analysis is so important! Our decision to emphasize on software details and providing code was sparked by an email I received from @harrisonspecht "Reanalysis of reanalysis".
Christophe Vanderaa@c_vanderaa14 Apr 2023
Replying to @c_vanderaa
Software details do matter! For instance, the same KNN algorithm implemented in two pieces of software leads to different results, because they either impute by samples (cells) or by variable (proteins). Here's the impact on cell correlations.
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Harrison raised the points that the correlations he computed were not the same as the correlations we showed in our previous article, while we were both processing the exact same dataset with the exact same algorithms (or were we?) !
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Because the @slavovLab does such a nice job of providing the code to analyze their data, I could quickly identify that we were KNN imputing by variable and Harrison was KNN imputing by sample. This would have taken me ages if I add to guess this from a blurry methods section!
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