Did you know most clinical genomics runs on research-grade code? That code has carried the field far, but benchmarking once isn't the same as verifying across versions, edge cases, & clinical use. @nilshomer.com on tool-level verification becoming routine: blog.fulcrumgenomics.com/p/benchmarki...

Benchmarking is not validation

Clinical genomics runs on research-grade code. We need to validate it.

blog.fulcrumgenomics.com

CRISPR off-target search can find the right locus while hiding plausible alignments within it. I wrote about how Sassy v0.2.5 uses recursive backtracking to report every reasonable alignment—more than 9× as many in under 30 seconds. blog.fulcrumgenomics.com/p/why-crispr...

Why CRISPR Off-Target Search Should Report Multiple Alignments Per Locus

How Sassy enumerates every reasonable alignment without sacrificing runtime

blog.fulcrumgenomics.com

DivRef is a resource for including common human variants and haplotypes in CRISPR off-target searches. I rebuilt the generation workflow to make its inputs, assumptions and population choices easier to inspect and change. blog.fulcrumgenomics.com/p/a-crispr-o...

A CRISPR off-target search is only as good as the sequences it searches

Rebuilding DivRef so CRISPR off-target searches can account for human variation

blog.fulcrumgenomics.com

A CRISPR off-target search cannot report a sequence it was never given. @ameynert.bsky.social explains how DivRef brings common human variants and haplotypes into the search space—and how her rebuild complements @timd.one work on Sassy. Read Alison’s post: blog.fulcrumgenomics.com/p/a-crispr-o...

A CRISPR off-target search is only as good as the sequences it searches

Rebuilding DivRef so CRISPR off-target searches can account for human variation

blog.fulcrumgenomics.com

grep is indispensable—until you need to search FASTQ files correctly. We created a hands-on guide on Sandbox.bio for searching sequencing reads and paired-end data directly in your browser 👇

Robert Aboukhalil@robert.bio · 3w ago

grep is a fantastic tool, but it doesn't really work on sequencing data: it breaks when the pattern is in the read name, and doesn't support paired-end FASTQs. Thanks to @nilshomer.com, we have a new interactive guide on using fqgrep to find patterns in FASTQ files: ➡️ sandbox.bio/tutorials/fq...

Reporting one alignment per locus can commit a CRISPR off-target analysis to one scoring model too early. @timd.one explains how Sassy v0.2.5 enumerates every reasonable alignment while keeping runtime fast: >9× as many alignments in under 30 seconds. blog.fulcrumgenomics.com/p/why-crispr...

Why CRISPR Off-Target Search Should Report Multiple Alignments Per Locus

How Sassy enumerates every reasonable alignment without sacrificing runtime

blog.fulcrumgenomics.com

In Q2 Fulcrum Field Notes: @nilshomer.com on AI rewrites and minibwa, @tfenne.bsky.social on Riker for deep sequencing QC and old bioinformatics plumbing. Read the Q2 issue: resources.fulcrumgenomics.com/q2-fulcrum-f...

New on the Fulcrum blog: minibwa, a faster mapper from @lh3lh3.bsky.social and our @nilshomer.com Its speed is great, yes, but more interesting is the decision to revisit BWA-MEM as infrastructure – keep what still works, change what limits performance, then test downstream impact. shorturl.at/xxqeI

Minibwa: alignment is never solved

Heng Li and Nils Homer revisit BWA-MEM with a faster mapper for short reads, accurate long reads, and bisulfite sequencing data.

blog.fulcrumgenomics.com

Pipeline release! nf-core/fastquorum v2.0.0 - 2.0.0! Please see the changelog: https://github.com/nf-core/fastquorum/releases/tag/2.0.0

Release 2.0.0 · nf-core/fastquorum

What's Changed New Features Add non-random UMI correction via fgbio CorrectUmis, enabled by an optional umi_file column in the samplesheet #145 Add optional library_id, lane, and flowcell samplesh...

github.com

Minibwa is a hybrid of bwa-mem and minimap2 and the successor of bwa-mem for short-read mapping. ~4X/2.5X as fast as bwa-mem/bwa-mem2 for WGS reads at comparable accuracy. Native support of directional bisulfite-seq. Applicable to long reads. Preprint at arxiv.org/abs/2606.15357

@tfenne.bsky.social has a new post on tuning up bioinformatics’ old plumbing: HTSJDK, jlibdeflate, chelae, mako, GLIMPSE, verifyBamID, bwa-mem3, and the low-level tools behind everyday workflows. Improve the infrastructure. Validate the behavior. Let the gains compound. Blog post 👇

The Scantox + LatchBio + Fulcrum webinar on the new Scantox DuplexSeq™ Mutagenesis App is now available on demand. @moonlight.bio covers Fulcrum’s approach to rebuilding and validating the bioinformatics pipeline so the infrastructure could improve without changing the science. Link below👇

Open-source bioinformatics works best when the tools are fast, inspectable, and reproducible. Our recent releases cover UMI workflows, sequencing QC, reference identification, ECS analysis, and HGVS parsing. See the one-page overview: shorturl.at/uo8iX

@nilshomer.com joined Rob Patro, @ewels.bsky.social, & others to talk AI-assisted bioinformatics rewrites on the OMGenomics show. The AI-assisted rewrite is the easy part. It is proving correctness, finding edge cases, and being around to support the tool later that’s harder. youtu.be/0o2XnEBDxrI

I interviewed 5 bioinformatics experts about AI rewrites

YouTube video by OMGenomics

youtu.be

New release of fgbio today. Major change is to pull in HTSJDK 5 for big bumps to BAM and CRAM read/write performance, as well as full CRAM 3.1 read/write support! github.com/fulcrumgenom...

I've seen lots of AI rewrites in bioinformatics lately, and I’m concerned because LLMs can be confidently wrong. What do the best tool builders do to make sure their rewrites are correct? How can we tell if a rewrite is flawed? I interviewed 5 scientists to find out: youtu.be/0o2XnEBDxrI

I interviewed 5 bioinformatics experts about AI rewrites

YouTube video by OMGenomics

youtu.be

Over the last few weeks I've been exploring writing a new short-read adapter trimming tool after running into frustrations with existing tools. Yesterday I made it public and pushed the first release to bioconda: github.com/fulcrumgenom...

GitHub - fulcrumgenomics/chelae: Fast, highly accurate, read-trimming for NGS data.

Fast, highly accurate, read-trimming for NGS data. - fulcrumgenomics/chelae

github.com

The bioinformatics community has been waiting for a modern home for the DuplexSeq method. We supported Scantox in migrating the pipeline onto Latch, validated outputs against TwinStrand's original datasets, and rebuilt the foundation so it can keep evolving with current research. shorturl.at/VmqBT

Scantox Upgrades DuplexSeq™ Bioinformatics with Cloud-Based Mutagenesis App -

Scantox launches cloud based App, for its DuplexSeq™ Mutagenesis Assay kits and services. Click to learn more.

scantox.com

Deep QC should run on every sequencing dataset. In a new post, Fulcrum co-founder @tfenne.bsky.social explains why he built Riker, a modern successor to Picard designed to make rich sequencing QC fast enough to run every time. Blog: shorturl.at/oUTXk Repo: github.com/fulcrumgenom...

Oncology pipelines don’t stay where they were first built. They move across teams, infra, and timelines, and can start to get brittle. So we built twistcgp with @twistbioscience.com as an nf-core-based workflow for analyzing data from the Twist Oncology DNA CGP Panel. github.com/fulcrumgenom...

GitHub - fulcrumgenomics/twistcgp: Nextflow pipeline for Twist Comprehensive Genomic Profiling (CGP) panel analysis

Nextflow pipeline for Twist Comprehensive Genomic Profiling (CGP) panel analysis - fulcrumgenomics/twistcgp

github.com

At #AGBTAg26, @nilshomer.com will present our work with @broadinstitute.org , @umasschan.bsky.social, and Darwin's Ark on building a comprehensive imputation reference panel for domestic cats. See the flash talk today at 4:30pm during the Plenary, or catch poster #128 during the poster sessions.

With CacheDNA we benchmarked ensilication for room‑temp DNA storage vs −80°C. Results: -100% concordance on clinical FFPE lung panel down to ~2% VAF -65% more artifactual C>T mutations at -80C than ensilication in WGS What this means for oncology, TMB, and global genomics: shorturl.at/ZqUck

Ambient DNA Preservation Without Compromising Sequencing: Our Role in Evaluating Ensilication

Whole‑genome analysis of storage-induced artifacts in tumor and normal DNA

blog.fulcrumgenomics.com

We built fgbio years ago to support UMI-aware sequencing. As datasets grew, the single-threaded design started to show its limits. fgumi is the next iteration: same expected outputs, rewritten for performance and scale. github.com/fulcrumgenom... Blog post details below👇

GitHub - fulcrumgenomics/fgumi: High-performance UMI tools for NGS data analysis

High-performance UMI tools for NGS data analysis. Contribute to fulcrumgenomics/fgumi development by creating an account on GitHub.

github.com

Ever receive a BAM aligned to “GRCh38” and realize that could mean several different references? We just released ref-solver, a tool that identifies the reference genome behind BAM/CRAM/FASTA files by comparing sequence dictionaries to known builds. 🔗 whatsmygenome.fulcrumgenomics.com Read more 👇

HGVS parsing sounds straightforward until you run it at scale across real clinical variants. We just released ferro-hgvs, a Rust-based parser/normalizer that processes millions of variants per second & handles many tricky edge cases other tools struggle with. 🔗 hgvs.acgt.bio Details in blog post👇

Bioinformatics tools usually emit the final result and discard everything that led to it. That missing signal is exactly what ML models need to learn from. Fulcrum co-founder @nilshomer.com makes the case that next generation tools should be AI-ready. 🔗 blog.fulcrumgenomics.com/p/your-bioin...

Your Bioinformatics Tools Need to be AI-Ready

If you're not building tools that emit rich data for machine learning, you're wasting your compute.

blog.fulcrumgenomics.com

Our #bioinformatics leader & VP of Ops, @moonlight.bio, will be at #PMWC26 March 4–6 in Santa Clara. PMWC continues to push the field toward turning complex biological data into real decisions. Clint will be on-site connecting with teams advancing #genomics and #PrecisionMedicine.

Open-source (nf-core–based) workflow built with @twistbioscience.com for the Twist Oncology DNA CGP Panel is now public on GitHub. Portable across local/HPC/cloud. SNVs, indels, CNVs, TMB, MSI, VEP+CIViC, QC.

@tfenne.bsky.social and @nilshomer.com are on the ground at #AGBT2026 this week. Big data. Tight timelines. Real decisions. #Bioinformatics is where complexity becomes something teams can actually use. If you’re here, let’s connect.

One week to #AGBT2026. #Genomics data keeps growing. Pipelines keep multiplying. Turning results into something usable for research or the clinic? Still the hard part. From a #bioinformatics lens, what do you want to hear more about? Vote below