Assist. Prof. leading the Computational Biomedicine Group at @uniinnsbruck • Data scientist at @DiSC_uibk: precision medicine and cancer immunotherapy • Mother
Innsbruck
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📢New preprint alert: #Benchmarking second-generation methods for cell-type #deconvolution of #transcriptomic data
doi.org/10.1101/2024.06.10.5…
A thread 🧵👇
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Single-cell RNA sequencing generates detailed maps of changing cells, and the new scLS framework helps identify important gene activity patterns that drive development and disease. - @waseda_univ rna-seqblog.com/the-lomb-sca…
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RNA sequencing with Rectangle recovers detailed cell type information from bulk RNA sequencing data. The approach supports biomarker discovery and large-scale studies without single-cell sequencing for every sample. @uniinnsbruck @DiSC_uibk rna-seqblog.com/rectangle-ro…
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Rectangle: robust and scalable multiscale deconvolution informed by single-cell RNA sequencing data biorxiv.org/content/10.64898…
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GitHub - omnideconv/spacedeconv: A unified interface to spatial transcriptomics deconvolution tools github.com/omnideconv/spaced…
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GitHub - omnideconv/spacedeconv: A unified interface to spatial transcriptomics deconvolution tools github.com/omnideconv/spaced…
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We provide the scientific community with an ecosystem of tools and resources, #omnideconv, that strongly simplifies the application, benchmarking, and optimization of deconvolution methods: omnideconv.org
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Benchmarking second-generation methods for cell-type deconvolution of transcriptomic data biorxiv.org/content/10.1101/… 🧬🖥️🧪
omnideconv #Rstats pkg github.com/omnideconv/deconv…
Nextflow pipeline github.com/omnideconv/deconv…
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Great work on the benchmarking study! ️ I'm looking forward to exploring the omnideconv package and learning more about cell-type deconvolution of transcriptomic data.
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Thank you for highlighting our work! 🙏
#spacedeconv preprint is available at:
researchsquare.com/article/r…
#RNAseq is unlocking new ways to study tissue architecture, giving scientists critical insights into disease development. With tools like spacedeconv, researchers can now map out how cells interact, paving the way for breakthroughs in cancer @uniinnsbruck rna-seqblog.com/spacedeconv-…
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Many thanks to @tangming2005 for highlighting our work!
In a joint effort with @itisalist lab, we have developed 2 additional packages for:
- scRNA-seq-informed deconvolution, #omnideconv:
shorturl.at/fjKMU
- spatial deconvolution, #spacedeconv:
shorturl.at/swFIP
4. immunedeconv, an R package for unified access to 10 computational methods for estimating immune cell fractions from bulk RNA sequencing data.buff.ly/458voBv
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Closing 2024, scverse celebrates incredible growth and collaboration! Huge thanks to everyone on this journey and our dedicated core team & management board (@fabian_theis, @Francesca_Fin_, @OliverStegle , @YosefLab, @panos_roussos, @nomad421). Here’s to an even brighter 2025!
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anndata 0.11 is out now: anndata.readthedocs.io/en/st…! We have some great new features to highlight as well as some breaking changes to look out for.
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1/10 PREPRINT MONDAY at the SchubertLab
Benchmarking TCR-Epitope Predictors with ePytope-TCR (doi.org/10.1101/2024.11.06.6…)
Short-Summary:
- 18 pre-trained public methods
- evaluated on 2 benchmarking datasets
- for repertoire annotation & cross-reactivity prediction
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NovumRNA: accurate prediction of non-canonical tumor antigens from RNA sequencing data biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
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Are you (or is someone you know) teaching AI / ML / Deep Learning this year? My forthcoming book (freely available at udlbook.com) will save you a lot of time. This thread will show you why.
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🚀 New Tool Alert! 🚀
PENGUIN 🐧is finally published in @CSB_Journal : PENGUIN is a rapid, efficient, and user-friendly tool for denoising and normalizing multiplexed spatial proteomics images! 🔬✨
🔗sciencedirect.com/science/ar…
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TCR lovers, we are delighted to share our benchmarking of TCR specificity tools using an harmonized aggregation of public databases. biorxiv.org/content/10.1101/…
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🚀 Proud to launch ⭐Path2Space⭐ — the first AI to discover spatial biomarkers for cancer treatment!
It predicts spatial gene expression from histopathology, enabling large-scale tumor microenvironment profiling.
biorxiv.org/content/10.1101/… 🧵1/11
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**Please Retweet (Re-X?)**
🔥Postdoc #jobs in Spatial / Single Cell Omics
Looking to become a #leader in #SpatialBiology?
Love NGS & #MachineLearning? #Positions @harvardmed @broadinstitute
linkedin.com/jobs/view/40389…
#hiring #lab #boston #research #aiml #biotech #Science
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RNA sequencing depth guidelines for the study of alternative splicing biorxiv.org/cgi/content/shor… #biorxiv_bioinfo
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