Koen Van den Berge
koenvdberge.bsky.social
Koen Van den Berge
@koenvdberge.bsky.social

Statistical genomics. Currently working on single-cell data analysis in context of drug development. Previously post-doc at UC Berkeley and Ghent University.

Environmental science 36%
Biology 19%

We're looking for a post-doc to support target discovery in lymphoma using single-cell and spatial 'omics modalities.

You will be embedded in our Discovery Statistics organization, and supported by myself and colleagues. Feel free to reach out for any additional information.

tinyurl.com/36uyca7f
Post Doc PD DD PCCD
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments...
tinyurl.com
After two weeks, I'm finally done!

In this post, I explain different approaches for solving linear regression in R: directly, using QR, singular value and Cholesky decompositions, and do some benchmarking for comparison with in-built approaches.

thomvolker.github.io/blog/2506_re...

Reposted by Koen Van Den Berge

Here it is! Bonsai. Now there is really no more excuse for using t-SNE/UMAP. Bonsai not only makes cool pictures of your data. It actually rigorously preserves its structure. No tunable parameters. Incredible work by @dhdegroot.bsky.social.
I'm so excited about this!
www.biorxiv.org/content/10.1...
Bonsai: Tree representations for distortion-free visualization and exploratory analysis of single-cell omics data
Single-cell omics methods promise to revolutionize our understanding of gene regulatory processes during cell differentiation, but analysis of such data continues to pose a major challenge. Apart from...
www.biorxiv.org

Reposted by Koen Van Den Berge

New preprint from Ajay Nadig @nadigajay.bsky.social in Luke O'Connor's lab, with "a suite of statistical tools for formally modeling distributions of DE effects from RNA-seq experiments, including Perturb-seq"

www.biorxiv.org/content/10.1...
Transcriptome-wide characterization of genetic perturbations
Single cell CRISPR screens such as Perturb-seq enable transcriptomic profiling of genetic perturbations at scale. However, the data produced by these screens are often noisy due to cost and technical ...
www.biorxiv.org
Dire wolves were not close relatives of gray wolves. They last shared a common ancestor more than 5 million years ago. What Colossal has done is make something new and slapped a dire wolf sticker on it, as if an organism equals a hypothetical genome.
Dire Wolves Were Not Really Wolves, New Genetic Clues Reveal
The extinct giant canids were a remarkable example of convergent evolution
www.scientificamerican.com

We've just released radEmu v2.0.0 🥳🦤😻

`remotes::install_github("statdivlab/radEmu")`

A huge thanks to users for sharing their requests and questions, and to the maintenance team (Sarah and @davidandacat.bsky.social ) for their time and commitment!

Release notes: github.com/statdivlab/r...

Reposted by Koen Van Den Berge

In Science, researchers detail a nanoscale-resolution reconstruction of a millimeter-scale fragment of human cerebral cortex, giving an unprecedented view into the structural organization of brain tissue at the supracellular, cellular, and subcellular levels. scim.ag/3FvpAKy #BrainAwarenessWeek

Reposted by Koen Van Den Berge

I am happy to announce our new paper "Univariate-guided sparse regression". It's a new lasso that leverages the signs and magnitude of univariate coefficients .
Sparser and more interpretable than the lasso. We're excited! arxiv.org/abs/2501.18360
R: github.com/trevorhastie...
Univariate-Guided Sparse Regression
In this paper, we introduce ``UniLasso'' -- a novel statistical method for sparse regression. This two-stage approach preserves the signs of the univariate coefficients and leverages their magnitude. ...
arxiv.org

Reposted by Koen Van Den Berge

This is long overdue, but over the winter break we were finally able to write up our sgdGMF paper:
arxiv.org/abs/2412.20509

We present a stochastic gradient descent method that allows to efficiently and very quickly estimate latent factors for, e.g., dimensionality reduction of single-cell data

Reposted by Koen Van Den Berge

Very excited to announce that the single cell/nuc. RNA/ATAC/multi-ome resource from ENCODE4 is now officially public. This includes raw data, processed data, annotations and pseudobulk products. Covers many human & mouse tissues. 1/

www.encodeproject.org/single-cell/...
Single cell – ENCODEHomo sapiens clickable body map
www.encodeproject.org

Reposted by Koen Van Den Berge

A few papers I think worth reading. Mostly open access.

Causal inference is hard:

www.nature.com/articles/s41...
Causal inference on human behaviour - Nature Human Behaviour
In this Review, Drew Bailey et al. present an accessible, non-technical overview of key challenges for causal inference in studies of human behaviour as well as methodological solutions to these chall...
www.nature.com

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Have you been thinking hard about statistical modelling of scATAC-seq data? (No.)

Luckily for you, @aaronkwc.bsky.social has!

Aaron will help you grok:
What's going on?
What is TF-IDF?
Is there really single-cell level chromatin information?

Check it out 👇
www.biorxiv.org/content/10.1...

🧪🧬💻
Going beyond cell clustering and feature aggregation: Is there single cell level information in single-cell ATAC-seq data?
Single-cell Assay for Transposase Accessible Chromatin with sequencing (scATAC-seq) has become a widely used method for investigating chromatin accessibility at single-cell resolution. However, the re...
www.biorxiv.org

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge

Reposted by Koen Van Den Berge