Manu Setty
@SettyM
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Assistant Professor, @fredhutch @HutchBasicSci & Translational Data Science IRC. Computational biologist | Single-cell data analysis and modeling.
Seattle, WA
Joined January 2011
Very excited to have Mellon out in @naturemethods today!
Mellon accurately estimates cell-state densities using high-dimensional single-cell data, unveiling regulatory dynamics and mechanisms in cell differentiation. https://t.co/3xfstDZRqr
@SettyM @fredhutch
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My journey from south India to biomedical researcher in the United States is not too dissimilar to the one taken by @KamalaHarris mother. With deep gratitude for all the opportunities I have been provided, my vote is for respect, dignity and a new way forward
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16 years after arriving in the United States, I am honored and proud to cast my first vote in a Presidential election to a daugher of immigrants, @VP @KamalaHarris !
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What happens when a high school science teacher spends her summer learning computational biology and coding basics ? Biology and Forensics teacher Dr. Rama Devagupta wrote about her experience in the Setty Lab . Check out our Hutch Teacher Fellowship Blog:
sites.google.com
High School Science Teacher Devotes Her Summer to Learn Computational Biology Remotely from India
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Are you an early career scientist who wants to pursue a research project in the lab of a Fred Hutch Computational Biologist mentor? If yes, then the #MahanFellowship is for you. Apply by Dec. 20, 2024! Learn more: https://t.co/dkFkYT9ROs
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Awesome week at Bertinoro #CompBio meeting! Exciting times for cancer evolution x tumor microenvironment! Thank you @SohrabShah @jens_lagergren
Wonderful Bertinoro Computational Biology meeting, Russel Schwarz summarizing a lot of effort going on in the field of modeling tumor biology in the fresco room. Taking place among puring rain around the hill. Thank you for the invitation @SohrabShah @jens_lagergren @elhamazizi
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Join us in this exciting symposium to learn about post-doc opportunities at @HutchBasicSci
Calling everyone interested in #postdoc opportunities @HutchBasicSci! Join us at the Pathfinders: Postdoc Recruitment Symposium @FredHutch. Explore our research programs, present your work, and network with current postdocs and faculty. Apply by July 8:
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@naturemethods Re-upping the tweetorial from our bioRxiv post here:
Super excited to present our algorithm, Mellon for computing densities in single-cell landscapes. https://t.co/VFzfUixocA
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Terrific work by @danielcjones in @EvNewell1 lab- Proseg is our go-to cell segmentation for all spatial transcriptomics data!
Using in situ spatial transcriptomics? Try Proseg, @danielcjones’s new cell segmentation method based on probabilistic and Cellular Potts modeling. Great for @vizgen_inc Merscope, @10xGenomics Xenium, and @nanostringtech CosMx data. Preprint & code: (1/n) https://t.co/OJfE3nbJLj
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The #MahanFellowship supports young scientists in the early stages of their careers. We offer fellows a 21-month stipend as they pursue their proposed research project, alongside a mentor in one of our Herbold Computational Biologist labs. Apply today:
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1/8 Today we highlight exciting work from the @SettyM lab that introduces Mellon, a new approach for quantifying cell-state densities from single-cell data with a particular focus on differentiating systems.
biorxiv.org
Cell-state density characterizes the distribution of cells along phenotypic landscapes and is crucial for unraveling the mechanisms that drive cellular differentiation, regeneration, and disease....
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Say hello to CellRank 2, a unified framework for data view independent fate mapping! Have a look at our preprint on bioRxiv ( https://t.co/bJkneo1fZj) and check out @MariusLange8’s tweetorial as well! @HelmholtzMunich @CompHealthMuc @TU_Muenchen @fabian_theis @dana_peer (1/14)
biorxiv.org
Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or RNA velocity to reconstruct state-change trajectories. However, trajectory...
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Deadline this Friday!
Calling all PhD (or equivalent) students within 2 years of graduation or who have graduated in the last year: Join us for an opportunity to visit with faculty at @FredHutch and hear about career opportunities at this world-renowned institution: https://t.co/7LziDWiVSs
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Mellon repository is available at https://t.co/u162GZhS95, and the pipeline for primed and lineage-specific peak identification (along with other utilities for ATAC metacells) is available at:
github.com
Snakemake pipeline for scATAC metacell utilities such as primed and lineage specific scores, chromVAR, in-silico ChIP - settylab/atac_metacell_utilities
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We have implemeneted Mellon as a general purpose Gaussian Process function estimator with a number of utilities including super-fast gene trend estimation along pseudo-time for thousands of genes.
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Finally, Mellon is blazing fast - density for 100k cells takes only a few minutes with a (near) linear dependence of computation time on number of cells.
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The function is also differentiable, which means we can interpolate the change in density too! The measured time points are grey lines at the bottom - all other times are interpolated densities and changes.
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Mellon framework can be extended to infer a density function that is continuous in both cell-state and time. We use this to interpolate densities between measured time points in time-series datasets. Thanks to @MarioniLab for the repo to download data: https://t.co/abRC2g0nHy !
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We also developed a procedure to disentagle primed and lineage-specific peaks from single-cell ATAC data (rather than one gene score), and show that enhancer priming plays a role in driving low-density transitions.
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