Malte Luecken @MDLuecken
Luckylab, Computational Biologist, Data integrator, Human Cell Atlasser, Single cell, Lung, Floorballer linkedin.com/in/malte-l%C3%… Munich, Bavaria Joined February 2018-
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Excited to share Nicheformer! Led by @Alejandro__TL & @AnnaCSchaar, Nicheformer is a foundation model for single-cell & spatial omics. Its innovation is going beyond disassociated analysis to capture & predict local tissue context at single-cell level. biorxiv.org/content/10.110…
How to link single-cell diversity and the emergence and maintenance of robust multicellular processes in developed tissues? 🤔 What can we learn about multicellular coordination in tissues from single-cell omics data? Read about our view: arxiv.org/abs/2403.06753
1/7 Want to know which spatial patterns correlate with your disease of interest? Check out our preprint introducing GraphCompass, a Python-based framework for the differential analysis of spatial organization across conditions! bioRxiv: biorxiv.org/content/10.110…
Our latest out today in @Nature. We profiled 12 million single cells from mouse embryos spanning gastrulation to birth, defined cell type tree from zygote to birth, and unexpectedly found crazy fast changes within first hour of extrauterine life. OA PDF: rdcu.be/dyDAg
Our latest out today in @Nature. We profiled 12 million single cells from mouse embryos spanning gastrulation to birth, defined cell type tree from zygote to birth, and unexpectedly found crazy fast changes within first hour of extrauterine life. OA PDF: rdcu.be/dyDAg
Really excited that this paper is out! Thanks a lot to @SchillerLab who gave us the opportunity to contribute to the analysis by contextualizing ex vivo PCLS data with the human lung cell atlas. Great work by @shitov_happens
Really excited that this paper is out! Thanks a lot to @SchillerLab who gave us the opportunity to contribute to the analysis by contextualizing ex vivo PCLS data with the human lung cell atlas. Great work by @shitov_happens
Big milestone - single cell genomics of perturbations in human lung tissue. We work on scaling this approach towards `phenoscaping´ the plasticity of lung tissue states. @discovAIR_HCA @CPC_Imaging @schniering_j @niklasjlang @MDLuecken @fabian_theis bit.ly/3Nee3Au
Big milestone - single cell genomics of perturbations in human lung tissue. We work on scaling this approach towards `phenoscaping´ the plasticity of lung tissue states. @discovAIR_HCA @CPC_Imaging @schniering_j @niklasjlang @MDLuecken @fabian_theis bit.ly/3Nee3Au https://t.co/X1LsgvIbMV
Today our Human Lung Cell Atlas (HLCA) paper came out in Nature Medicine nature.com/articles/s4159…! The HLCA includes 2.4M cells from 486 individuals and 49 datasets. Check out this tweetorial to learn more about how we built it, and how you can use it (1/21)
I'm very happy to share our new study published today in @ScienceAdvances showing how Early Life Adversity leads to social deficits later in life. It was great to work on this one with my best friends Aron Kos and @JulienDine at @alon_chen_lab. science.org/doi/10.1126/sc…
Is binarization of scATAC-seq data really necessary? The conclusion from our analysis is that a quantitative treatment is in fact beneficial. Now out in Nature Methods! @gagneurlab @fabian_theis nature.com/articles/s4159… Many additions since the preprint 👇(1/n)
Really impressive work by @emmamarydann on how to best use reference atlases to perform case-control analyses on new datasets. Building large, comprehensive reference atlases matters for better batch-correction performance!
Really impressive work by @emmamarydann on how to best use reference atlases to perform case-control analyses on new datasets. Building large, comprehensive reference atlases matters for better batch-correction performance!
10 benchmark papers on single-cell data 👇 🧵
Malte @MDLuecken presenting HCA integration team approach and state @humancellatlas meeting. #hca2023gm.
Neil Henderson talking about getting liver samples from Prometheus to increase the diversity of samples in the HCA… unfortunately no luck getting samples from eternal damnation #HCA2023GM impressive science too :).
Aviv kicking off #HCA2023GM with a great list of questions for current and future integration efforts! Some of these we have encountered in the HCA integration team, others are great tasks for the future :). Looking forward to discussions at the meeting!
In case you missed the announcements - the integrated cell atlas of the lung in Health and Disease is finally out. Kudos to Drs Sikkema, Nawjiin, Leucken, Theis & all members #HCLA for this Herculean effort, and yes, Truman was right nature.com/articles/s4159…
A #single-cell atlas of the human #lungs, integrating data from 2.4 million cells from 486 individuals and including samples from healthy and diseased lungs, provides a roadmap for generating organ-scale cell atlases. @SikkemaLisa @MDLuecken @fabian_theis nature.com/articles/s4159…
Congratulations to all involved in creating the first integrated Human Lung Cell Atlas. This fabulous international collaborative effort will provide a great resource for researchers, and is a milestone towards the full #HumanCellAtlas. @NatureMedicine nature.com/articles/s4159…
Congratulations to all involved in creating the first integrated Human Lung Cell Atlas. This fabulous international collaborative effort will provide a great resource for researchers, and is a milestone towards the full #HumanCellAtlas. @NatureMedicine nature.com/articles/s4159…
This was a true team effort! Such a pleasure to work with super-talented students like @SikkemaLisa and scientists like @MDLuecken @Misharin_lab & @fabian_theis! Support from @discovAIR_HCA @cziscience and @Longfonds and mostly my lab - they’re the best! @BiotripeX @Aurore__Gay
This was a true team effort! Such a pleasure to work with super-talented students like @SikkemaLisa and scientists like @MDLuecken @Misharin_lab & @fabian_theis! Support from @discovAIR_HCA @cziscience and @Longfonds and mostly my lab - they’re the best! @BiotripeX @Aurore__Gay
An amazing resource + innovative use of AI/ML to integrate and also enabling users to query single-cell atlases. Kodus to @SikkemaLisa @MDLuecken and everyone else. Check new tutorial on how to map your data on to HLCA using scArches: docs.scarches.org/en/latest/hlca…
An amazing resource + innovative use of AI/ML to integrate and also enabling users to query single-cell atlases. Kodus to @SikkemaLisa @MDLuecken and everyone else. Check new tutorial on how to map your data on to HLCA using scArches: docs.scarches.org/en/latest/hlca…
The main discovAIR output finally in print today!!! Such an accomplishment by the Lung Bionetwork of the @humancellatlas and a superb resource for the respiratory community @SikkemaLisa @MDLuecken @Misharin_lab @fabian_theis @MC_Nawijn @3Assembly @ATS_RCMB @Longfonds @cziscience
The main discovAIR output finally in print today!!! Such an accomplishment by the Lung Bionetwork of the @humancellatlas and a superb resource for the respiratory community @SikkemaLisa @MDLuecken @Misharin_lab @fabian_theis @MC_Nawijn @3Assembly @ATS_RCMB @Longfonds @cziscience
Fabian Theis @fabian_theis
29K Followers 446 Following Computational biologist @HelmholtzMunich, prof @TU_Muenchen & associate PI @sangerinstitute. Dad of 4 and mountain lover. Department news, see @CompHealthMuc
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19K Followers 544 Following MISSION To create comprehensive reference maps of all human cells as a basis for both understanding human health and diagnosing, monitoring and treating disease
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Florian Halbritter @cancerbits
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615 Followers 1K Following Assistant Professor@Ramananda College, Bankura University; Expertise in Bioinformatics # Former Postdoc @liu_universitet @FU_Berlin @UmeaUniversity; Shutterbug
Mathematics in Medica.. @MMLS_journal
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Javier Marchena Hurta.. @JavierMarchenaH
54 Followers 184 Following My goal is to make the world a better place.
Trishanta @_trishanta
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Francesco Tamiro @FTamiro
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Qiyu @yupines
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Manuel Lessi @lessi_manuel
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Lennard Halle @HalleLennard
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antisense. @razoralign
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1K Followers 366 Following Teaching machines to dream about single-cell data in expression and flow👩💻 PhD in Comp Bio, Research Minion, Karate Black Belt, California Newbie
Arjun Raj @arjunrajlab
25K Followers 2K Following Just another LLM. Tweets do not necessarily reflect the views of people in my lab or even my own views last week. https://t.co/fZAnUCqd12
Luciano Martelotto �.. @LGMartelotto
10K Followers 954 Following Sc/St-Omics pro-aficionado. Knowledge sharing is my thing. Views, opinions and comments are my own and do not represent those of my employer. Like/RT ≠ endorse
Simona Cristea @simocristea
7K Followers 496 Following Head of Data Science at Hale Center for Pancreatic Cancer | Group leader @DanaFarber @Harvard | We ❤️ genomics, evolution & LLMs | PhD @eth | 🇷🇴🇸🇪🇨🇭🇺🇸
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189 Followers 134 Following Postdoc at @UCBerkeley and @UCSF. Co-mentored by @Yoseflab and @yimmieg
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51K Followers 2K Following DeepAI is an experimental AI Product Lab. Sharing cool research at @arxiv_daily For product support email [email protected]
Jan Van den Bossche L.. @immunometlab
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Nils Eling @NilsEling
633 Followers 537 Following Senior Data Scientist @Novartis. Previously @BodenmillerLab and @MarioniLab. Interested in #singlecell, #multiplexedimaging, #rstats. Views are my own.
Kemal Inecik @kemalinecik
176 Followers 199 Following PhD Candidate specializing in "Machine Learning and Computational Biology" at TUM & Helmholtz, part of @fabian_theis research group
Micha Sam Brickman Ra.. @msbr89
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179 Followers 778 Following Crafting self-awareness 🚧. Views are my own ;)
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848 Followers 637 Following https://t.co/7CdTaHfVvY | Single-cell genomics, genome graphs, algorithm development | @broadinstitute @harvardmed
Matt Ritchie @mritchieau
3K Followers 2K Following Everything is R-some #rstats #bioconductor #genomics #singlecell #bioinformatics
Davide Risso @drisso1893
1K Followers 811 Following Statistician; Asst prof at @unipadova; (mediocre) soccer player :) Mastodon: @[email protected]
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Joseph Viviano @josephdviviano
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215 Followers 40 Following
MICCAI @MICCAI_Society
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98 Followers 145 Following
Valeh Valiollah Pour .. @valehvpa
151 Followers 334 Following PhD student @Stanford Genetics. I'm interested in applying ML, the right way, to questions in biology and medicine
Alex Coleman @alex__coleman
377 Followers 1K Following British/German biologist, biotechnologist & science manager. Grant manager @Helmholtz_AI @HelmholtzMunich. Enjoy science, travelling, sport, fine food & ale!@fabian_theis @Alejandro__TL @AnnaCSchaar Very cool. Some nice normalization & explicit batch correction aspects in the model. Liked the measured discussion section! Quite nice to not see overhyped claims. 1/
Excited to share Nicheformer! Led by @Alejandro__TL & @AnnaCSchaar, Nicheformer is a foundation model for single-cell & spatial omics. Its innovation is going beyond disassociated analysis to capture & predict local tissue context at single-cell level. biorxiv.org/content/10.110…
In order, where have you lived? Haifa Jerusalem San Francisco Ramat-Gan Pittsburgh New Haven Also had meaningful periods in Milano, Lund, New York, Tel Aviv
In order, where have you lived? Nottingham Cambridge Edinburgh Cambridge* New York* Cambridge* *to the closest city
That‘s how our @LungHealthMUC PIs meet. Happy to have the chance to work with some of the smartest, most creative people to create solutions for the future. We did some mean product design today!@AlionderCPC @Mkg_Lehmann @KapellosTS @CPC_Imaging @DiefenbacherL @MDLuecken
New concept 🤷♂️for lung cell atlas, seeing you there with Malte @MDLuecken and Richards @LungHealthMUC @HelmholtzMunich
SAVE THE DATE... New @ATS_RCMB Webminar from our Lung Single Cell Atlas Collection. Charting the Lung: Annotations and Ontologies Towards a Consensus Lung Cell Atlas Register here: thoracic.zoom.us/meeting/regist…
@lpachter I did not say the entire enterprise failed. I said the HCA / CZI failed in the specific task of an automated processing pipeline that works with a universal set of parameters to processes the data in a way that preserves biological integrity. Because that is a hard problem.
Delighted to share our latest paper out in @NatureMicrobiol on age-specific nasal epithelial responses to SARS-CoV-2. nature.com/articles/s4156… Amazing team science @Dr_ClaireSmith @teichlab @ucl @sangerinstitute @uclrespiratory
@lpachter @vitaliikl @maelouisewoods @satijalab @fabian_theis Agree 100%, but one can not make things monkey proof. A smart and thoughtful user is needed a the other end, and one that bothers to read methods sections and github documentation, which is not always the case
@dana_peer @vitaliikl @maelouisewoods @satijalab @fabian_theis Methods with multiple parameters that can be tuned can be very powerful, but only if developers provide guidelines for how to set the parameters (use cases, implications of changing parameters etc.) Otherwise such methods just become tools for overfitting.
As my lab develops Seurat, I wanted to share some thoughts on the important Seurat and scanpy package selection preprint from @Josephmrich/@lpachter 🧵
@satijalab @Josephmrich @lpachter Great response! Thanks for the years of work on an extremely useful and well maintained package.
@falexwolf @satijalab @Josephmrich @lpachter @scverse_team @ivirshup @fabian_theis I think that openproblems.bio could monitor such metrics as one of their tasks @MDLuecken
@satijalab @Josephmrich @lpachter The pragmatic question is whether there could be CI running on both Seurat & Scanpy that monitors metrics across versions the community agrees on: @scverse_team @ivirshup @fabian_theis @satijalab @Josephmrich Along with documentation that explains caveats and differences. Did…
We have developed Seurat over 5 versions and 10 years(!). Its an incredible privilege and a responsibility to build computational tools for the biological community. I'm so proud of what we've accomplished and enabled, and our commitment to continuing to develop and improve!
Moreover, while we have answered thousands of user issues and questions on Github and other venues, we should have centralized resource/paper that documents and justifies our implementation decisions and default parameter choices. We will prioritize this.
The outliers arise because Seurat adds a pseudocount at the pseudobulk level, and scanpy adds a smaller pseudocount at the cell level. There are arguments for both approaches, but there's no reason for us not to discuss and align.
For example, the scVI method (@YosefLab) is not deterministic, and different random seeds will affect downstream analysis. But as @_canergen has pointed out, true biological signal persists across runs with different random seeds. x.com/_canergen/stat…
Other hyperparameters don’t lead to higher NN reproducibility across different random seeds. We recommend using a fixed seed. If you have solutions on reducing this stochasticity, we are happy to discuss solutions or consider a PR.
Also as already mentioned by others, keep in mind that using "corrected" gene expression values for differential expression analysis is not recommended
This study evaluates how much results change before vs after scRNA-seq data integration when "batch effects" are insignificant. This is an important aspect to consider but in isolation not very useful to decide which integration method use with real data
In this preprint biorxiv.org/content/10.110… with @Sindri_e we compared seven widely used methods for batch correction of single cell RNA-seq data. We found that all but one of the methods introduce batch effects when there are none. 1/N
It implies that "no integration" is *always* better. In our recent benchmark using real data and multiple criteria (extending @MDLuecken work) we found that Harmony leads to strongest overcorrection, and this gets worse with celltype composition imbalance pubmed.ncbi.nlm.nih.gov/38287014/
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