No joke: you can get 4-field HLA typing from microarray data.
Most datasets already contain usable signal, it just hasn’t been fully resolved.
If you’ve written off array data for HLA, it’s worth a second look.
→ Want to test it? Reach out: info@benthic.bio
Large cohorts across biobanks and disease consortia were genotyped on SNP arrays.
Those datasets contain immune signals, but the genes themselves aren’t directly observed.
Angler infers HLA alleles and immune genes from SNP data so they can be analyzed across the full cohort.
🔗 benthic.bio/angler
Many GWAS signals land in the MHC but are hard to interpret.
In the Project MinE ALS study (29k cases), Angler imputed immune genes across 135k+ array samples and linked the signal to specific HLA haplotypes.
Full case study:
🔗https://shorturl.at/0FZhL
🍀 Working with arrays and immune genes this St. Patrick’s day?
Well, you’re in luck: you can try Angler Imputation on your own data, for free.
Just real results from real inputs.
🔗analysis.benthic.bio
#Genomics #HLA #Bioinformatics
Sequencing dominates new immune studies.
But plenty of legacy cohorts are array-based.
If unresolved HLA is slowing analysis, Angler can recover higher-resolution calls from SNP data you already have.
🔗 benthic.bio/angler
GWAS assumes independence + additivity.
The MHC runs on haplotypes, structure, and phase.
Collapse that into SNPs and you change the signal.
That’s why immune associations behave unpredictably across cohorts.
It comes down to the model. See what’s in ours at benthic.bio/angler
Reminder of our live 20-min walkthrough of Angler this Thursday 2/26.
We’ll show how Angler performs high-resolution HLA + immune-gene imputation from existing array or short-read data, including how confidence and ambiguity are handled.
Register: www.benthic.bio/angler-live-...
Immune-gene imputation doesn’t fail because “arrays don’t have enough SNPs.”
It fails when the reference/model can’t represent haplotypes + SVs.
Same data → totally different results.
Try our specialized immunogenome reference panel via Angler Imputation.
🔗benthic.bio/angler
Live Angler walkthrough Thurs (Feb 12).
Real inputs/outputs + how to interpret results and generate reports for HLA calls from array data.
Register: www.benthic.bio/angler-live-...
Pangenomes are no longer optional, but genome-wide graphs still lack the depth immune genes require.
We’ve built the Angler Reference Panel specifically to impute genotypes across 45 immune genes including HLA, MICA/B, and more.
Try it on some of your samples for free: analysis.benthic.bio
We’re hosting two live 20-min walkthroughs of Angler Imputation this month.
📅 Feb 12
📅 Feb 26
We’ll show how Angler performs high-resolution HLA + immune-gene imputation from array data, and how easy it is to do it yourself.
Register: www.benthic.bio/angler-live-...
Immune genes are “hard” because linear references can’t represent their diversity.
Graph-based references make those regions visible again.
That shift from linear to graph is foundational to everything we do at Benthic.
🔗benthic.bio/technology
#Genomics #HLA #Pangenome
There’s still time for our introductory pricing for first Angler projects.
If you want full HLA + 45 immune genes from array data, a few pilot slots are available.
Reach out if you want one.
Most HLA imputation tools focus on classical loci, 2-field resolution, and older reference panels.
Angler adds 45 immune genes, 3–4-field alleles, DP/DQ alpha chains, non-classicals, and a modern multi-ancestry reference — all in a simple web interface.
HLA imputation succeeds or fails based on the reference panel.
Older tools use limited loci + Euro-heavy haplotypes.
Angler uses multi-ancestry, long-read haplotypes across 45 immune genes — enabling full resolution even in the most polymorphic regions.
Array SNPs can recover high-res HLA because the MHC is built from long, conserved haplotypes.
Angler uses a multi-ancestry reference to impute alleles across 45 immune genes for comprehensive HLA typing from arrays.
Links in comments👇
📄https://doi.org/10.1371/journal.pcbi.1011718
🔗 benthic.bio/angler
A study from Finland shows arrays can support 97–100% accurate imputation for MICA, MICB, HLA-E/F/G UTRs across global ancestries.
This underpins Angler’s approach — extending it to 45 immune genes and 3–4-field HLA resolution through a modern reference panel.
Link in comments👇
Most array analyses only look at a few HLA loci — often just the beta chains.
Angler recovers complete high-res HLA + 40+ immune genes from arrays through a modern, easy web interface.
What does your array HLA coverage look like?
We're offering introductory pricing for first Angler projects starting in Q1.
If you’ve got array data and want full HLA + immune-gene coverage, now’s a good time to start.
DM for details.
We want to hear from lab teams planning HLA/immune gene work for 2026. If your lab is:
-Running arrays already & wants higher-resolution HLA
-Considering whether array + imputation can sit alongside your NGS panels
Replies/DMs welcome; we’ll follow up after with validation and integration details.
www.benthic.bio/_files/ugd/e...
In Case You Missed It: For Project MinE (ALS research), Angler re‑analyzed 135K+ arrays and 10K+ NGS datasets to fill MHC “dark regions” and fine‑map 3 novel HLA signals with no new lab work.
We’re offering intro pricing for first‑time projects using existing data. DM “intro pricing” for details.
Make the last of your 2025 budget work harder.
If you’ve got years of genotyping array data, Angler can turn it into >95%‑accurate 3‑field HLA typing across 45 immune genes, including non‑classical HLA, MICA/B, TAP1/2 and DRB3/4/5 CNVs.
Introductory pricing for first pilots—DM us for pricing.
Curious how we perform on your samples? Get in touch for a free demo.
That means a lab running arrays for any reason (transplant, pharmacogenomics, large cohorts) can bolt on high‑resolution HLA typing purely at the analysis layer.
