Johannes Köster

@johanneskoester.bsky.social

Professor for Bioinformatics and Computational Oncology University of Duisburg-Essen Author of Snakemake, founder of Bioconda

The plot is highly customizable by choosing marks, aggregation, color and size mappings and can be directly exported to publication ready SVG files. We also support exporting the specs back into a datavzrd view for easy reproducibilty and more tweaking.

We continue to improve bedder. It does interval intersections on VCF, BED, etc and lets users write python expressions on the intersection to drive output (including modifying VCF INFO fields). It will also use an index where possible to avoid extra parsing. Give it a go: github.com/quinlan-lab/...

Release Release v0.2.1 · quinlan-lab/bedder-rs

Changes in v0.2.1 Downloads bedder-static-linux-x86_64: Static binary for Linux x86_64 (no dependencies required) bedder-static-macos-x86_64-python3.13: macOS x86_64 binary built with Python 3.13 ...

github.com

We just released a new version of #alignoth that adds support for multiple bam tracks that will get vstacked. Also many convenience features suggested by @johanneskoester.bsky.social such as automatically creating an index for bam, fasta and vcf files if they dont exit. github.com/alignoth/ali...

GitHub - alignoth/alignoth: Creating alignment plots from bam files

Creating alignment plots from bam files. Contribute to alignoth/alignoth development by creating an account on GitHub.

github.com

#rustbio 4.0 has been released. It harmonizes the error handling, improves the API, makes gap-open/extend behavior in pairwise alignment more intuitive and in-line with the literature, improves GFF parsing, and allows incremental building of the rank-select datastructure. github.com/rust-bio/rus...

Release v4.0.0 · rust-bio/rust-bio

4.0.0 (2026-06-12) ⚠ BREAKING CHANGES Replace anyhow with typed thiserror errors (#674) Change Phase conversion methods to use TryFrom for better error handling (#625) for pairwise alignment, only...

github.com

A trend to keep an eye on are efforts to develop pocket AIs that can run offline on a single laptop. They're not nearly as powerful as what OpenAI or Anthropic offer, but if free offline options do enough to satisfy normie users the entire business case for so many massive data centres falls apart

It’s amazing how quickly we lose fluency in languages we don’t use frequently. I think many coders are going to find out the hard way that we don’t call programming languages that just for convenience. All to say I like this idea and will likely try the same (outside existing build-AI-to projects.)