Dylan Webster

Software product @10xGenomics. 🧬⚾🥋🎸

[Dylan Webster @DylanPWebster]

Awesome to see this out in the world! Very much looking forward to continuing our collaboration with Samuel Alber (@EggsAndSam7) and the @james_y_zou lab. More to come!

[10x Genomics @10xGenomics]

Exciting new work on AI agents in biology from @james_y_zou and @EggsAndSam7 in @naturemethods! As biology shifts from data generation to interpretation, AI agents can help with hypothesis generation. Excited to keep collaborating with the Zou Lab: https://t.co/HBfnRRFjJr

[Dylan Webster @DylanPWebster]

. @10xGenomics "GEM-X Flex generates reliable, comprehensive transcriptomic data from both fixed tissue and clinical biopsies. By overcoming some of the limitations of fresh and frozen tissue analysis, this protocol offers a robust solution for the broad implementation of scRNA-seq in clinical trials." 👀

[bioRxiv Genomics @biorxiv_genomic]

Performance of the 10X Genomics Flex Single-Cell Sequencing Assay and its Application to Overcome Challenges in Clinical Trial Samples https://t.co/WoahkRuAdL #biorxiv_genomic

[Rahul Satija @satijalab]

Excited to share VIPerturb-seq!

New tech from my lab which aims to improve the cost, data quality, and efficiency of single-cell CRISPR screens so that they are accessible to any lab - even at genome-wide scale

Preprint and 🧵 (1/): https://t.co/m8nleniSUD

[Dylan Webster @DylanPWebster]

Another point.☝️To move functional genomics into a new era of high-resolution screening for clinical cohorts, we need more than just scale—we need robustness.

Recent methods like VIPerturb-seq and ProPer-seq brilliantly demonstrate the advances of @10xGenomics Flex Apex in throughput and cost efficiency with cell lines. While cell lines are excellent for technology development and some modeling applications, the true barrier to large-scale, hypothesis-driven screening is the logistical complexity of handling real-world samples. For these samples, the value of a screen is defined by its reproducibility and its ability to interrogate primary human biology.

The 10x Genomics Flex platform is emerging as the standard for these high-value datasets, specifically due to its probe-based fixation workflow. This architecture solves the critical “sampling vs. processing” bottleneck, enabling the standardization required for large cohorts.

These recent studies illustrate why this workflow is essential for ensuring ROI on large-scale screens:

1. Standardization of Primary Cohorts (Zhu et al.) Conducting genome-scale screens in primary human cells (such as CD4+ T cells) has historically been limited by donor variability and batch effects. The Flex workflow allows for fixation at the point of collection, enabling teams to “bank and batch” samples. This effectively eliminates technical noise, ensuring that the variance observed is biological.
https://t.co/rFQJVB3a3Y

2. Multi-Modal Fidelity in Intact Tissue (Saunders et al.) Validating targets often requires more than just sequencing—it requires phenotypic context. Saunders et al. utilized this workflow to perform pooled genetic screens directly in intact mammalian tissue. The compatibility of Flex chemistry with fixed, permeabilized samples allows researchers to layer complex readouts (like imaging) with transcriptomics, capturing high-resolution data from complex tissue without the degradation issues common in traditional dissociation protocols.
https://t.co/AoXdXdZFdo

For R&D organizations, this represents a shift in operational capability. We can now design the highest resolution functional screens around the biology of the patient cohort, rather than the constraints of the assay.
#drugdiscovery #functionalgenomics #biotech #precisionmedicine #10xGenomics #singlecell

[Dylan Webster @DylanPWebster]

And another one. ☝️ Last week: ProPer-seq. This week: VIPerturb-seq from the Satija Lab.

Paper after paper is proving @10xGenomics Flex is the definitive engine for genome-scale perturbation screens. The new stats are wild:

🚀 440,000 cells per lane
🚀 50x throughput boost
🚀 65% more genes detected/cell

Routine genome-scale screens are here.
#singlecell #genomics #CRISPR #biotech #10xGenomics #virtualcell

[Dylan Webster @DylanPWebster]

@10xGenomics And this isn't even mentioning Zhu et al. from the Marson lab
(https://t.co/FMLdBwZ6W1) AND Perturb-Multimodal from Saunders et al. (https://t.co/P5HhzvXfK9)!

[Dylan Webster @DylanPWebster]

And another one. ☝️ Last week: ProPer-seq. This week: VIPerturb-seq from the Satija Lab.

Paper after paper is proving @10xGenomics Flex is the definitive engine for genome-scale perturbation screens. The new stats are wild:

🚀 440,000 cells per lane
🚀 50x throughput boost
🚀 65% more genes detected/cell

Routine genome-scale screens are here.
#singlecell #genomics #CRISPR #biotech #10xGenomics #virtualcell

[Dylan Webster @DylanPWebster]

@10xGenomics https://t.co/rlX6pKpH82

[Robert Stock @RobertStock6]

Of course that’s your contention. You’re a first-year analytics intern. You just got finished reading some Sabermetric historian—Bill James, probably. You’re gonna be convinced of that ’til next month when you get to the latest Pitching+ update, and then you’re gonna be talkin’ about how SIERA is the only "true" measure of skill because it accounts for the complexity of the batted ball profile to CSW rates.

You have no thoughts of your own. You’re just looking at a movement plot and trying to sound smart. You’re gonna realize in a couple of years that you spent all that time calculating "Expected FIP" based on a "Skill-Interactive" ghost, when you could’ve just looked at the K/BB ratio and seen the whole picture.

The sad thing is, in about five years, you’re gonna realize you’re not that bright. You’re gonna be talkin’ about Skenes’ "Expected ERA" while the real experts are just looking at a box score and realizing that if a guy doesn't walk people and he misses bats, he's gonna be fine.

You dropped $100,000 on a Data Science degree to learn how to run a regression on a pitcher's "luck," when you could’ve gotten the same predictive value for five cents in late charges by looking at a K/BB leader board at the public library.

[Dylan Webster @DylanPWebster]

It's amazing to see what awesome scientists can achieve with @10xGenomics GEM-X Flex. ProPer-seq highlights exactly how Flex’s probe-based, fixed-cell workflow overcomes cost and scale barriers—unlocking the massive datasets needed for large scale perturbation screens as an input to #virtualcell models.

#singlecell #genomics

[Elliot Hershberg @ElliotHershberg]

More exceptional technology from the Arc Institute:

"ProPer-seq faithfully reproduces gold-standard perturb-seq phenotypes while achieving 4-fold cost reduction and 50% increased gene detection per cell."

Seems like a big improvement (in cost and resolution) for one of the most central methods in modern functional genomics.

The required inputs to scale "virtual cell" models continue to plummet in cost...

[Dylan Webster @DylanPWebster]

Discover with 10x. Deepen with BioTuring.
Excited to partner with @bioturing to offer an advanced “next step” for researchers who need additional support in analysis as the @10xGenomics and BioTuring platforms advance together!

[10x Genomics @10xGenomics]

We are excited to announce a collaboration with @bioturing to support more seamless single cell and spatial data analysis. Read the full announcement: https://t.co/mlMjpfQt8s

[Matt Durrant @mgdurrant]

I recommend biology for anyone who is looking for meaning and beauty in their work!

[Geoffrey McDermott @gmcderm]

I would like to hope that this guy at the airport is reading a “spine tingling thriller” 😜

[Dylan Webster @DylanPWebster]

I can't stand techno-doom like Black Mirror and think it's pathological to civilization.

Technology is only as good as the motivation to use it. Optimism is what lands us on the moon and cures disease. Constant cynicism is just a self-fulfilling prophecy for stagnation and despair.

[Winston Timp @timp0]

Using @10xGenomics Genomics and @nanopore sequencing, we generated the first single-cell long-read dataset of the mouse hippocampus. For example, S100a16, a calcium-binding protein, has cell-type alternative isoforms undetectable with standard 10X 3’ short-read data:

[10x Genomics @10xGenomics]

Integrated #pathology annotation on the Xenium platform is now available! See for yourself how easy it is enhance your spatial insights by bridging pathology and #spatialtranscriptomics in a new tutorial. Check it out now: https://t.co/phR1KkLV4n

#AMPath2025

[Dylan Webster @DylanPWebster]

Excited to have a front seat @10xGenomics to see the breakthroughs that will follow from virtual cell models. And also to have had a small part in building the #singlecell #spatialbiology tools that will make this possible with data generation initiatives like the Billion Cells Project @officialbiohub
(https://t.co/MlzQoYTxUy).

[a16z @a16z]

Mark Zuckerberg says progress comes from inventing tools that let us observe the world in a new way, from the microscope to AI models that simulate life itself.

"Most major breakthroughs are basically preceded by the invention of a new tool to observe phenomena in a new way."

“And then you try to unlock those tools and give them to the scientific community to accelerate the pace.”

[Dylan Webster @DylanPWebster]

Awesome work Mike and Matt (and the entire Xenium software team) ! It's been great to see how the rapid advances in @10xGenomics Xenium software have impacted science in bringing this new technology to maturity quickly!

#singlecellspatial #insitu #genomics #bioinformatics

[10x Genomics @10xGenomics]

Explore our top #Xenium #insitu software improvements since 2022 in this blog, featuring a faster self-serve custom panel design portal, algorithms for more accurate, powerful cell segmentation & more. Check out what’s new here! https://t.co/dtXa7CbUtX