For multi-omics teams — no HPC engineer required

Every omics pipeline at cohort scale, in your AWS.

Any nf-core pipeline — public or private — plus NVIDIA Parabricks, AlphaDIA, DIA-NN, MetaMorpheus, and your own custom Slurm jobs, run as one managed cluster inside your own AWS account. Your data never leaves your VPC, every cohort autoscales onto the right GPU on spot, and your AWS & NVIDIA credits pay the compute. Not a pip install — a cluster operated for you.

3 design-partner slots · BYOC plans from $99/mo · free 30-day pilot

Any nf-core pipeline · public or private NVIDIA Parabricks · DeepVariant AlphaDIA · DIA-NN · MetaMorpheus BYOC — your data stays in your VPC

The open-source omics stack your team already runs

· · · · · · · · · · · ·
Time to a working omics cluster

Cluster live today. First cohort in 30 days.

AWS PCS, DIY 4 – 8 weeks
HPC engineer hire + ramp 12 – 24 weeks
Clusterra today
What runs

Your entire omics stack — one cluster, no DevOps team.

The open-source tools your team already runs, pre-built and Slurm-orchestrated in your own AWS. No HPC engineer to hire, no Nextflow executor to wire, no GPU drivers to chase. Submit a cohort; Karpenter picks the hardware.

01 / Any nf-core pipeline — public or private

Every nf-core / Nextflow pipeline, on Slurm — yours included.

Run any nf-core pipeline end-to-end — sarek, rnaseq, atacseq, scrnaseq, methylseq, the full catalog — or point us at your lab's private, in-house Nextflow pipeline. The Nextflow executor is wired to Slurm with managed S3/EFS staging; public or private, no pipeline-engine babysitting, and the cohort fans out across spot nodes automatically.

02 / GPU genomics — NVIDIA Parabricks

Parabricks GPU alignment + DeepVariant, hours not days.

NVIDIA Parabricks does BWA alignment and DeepVariant calling on the GPU. A 30× WGS sample (GIAB NA12878) runs in 2h 32m at $2.59 on g5 spot — SNP F1 0.9966 / INDEL F1 0.9934 against the hap.py truth set. Your NVIDIA Inception credits cover the GPU time.

03 / Proteomics — DIA & glyco mass-spec

AlphaDIA, DIA-NN, and MetaMorpheus — cohorts in parallel.

AlphaDIA and DIA-NN (v1.9.1 pinned, free) for DIA quant, MetaMorpheus for search and glycoproteomics. A timsTOF Ultra 2 HeLa DIA sample identifies 8,591 proteins in 13 minutes at $0.05 — and a 50-sample cohort runs in parallel, not serial.

04 / Single-cell

scanpy / single-cell pipelines on the same queue.

Single-cell analysis runs on the same managed cluster — same sbatch, same EFS, same per-job cost stamp. CPU-heavy or GPU-accelerated steps land on the right instance family without you choosing a partition.

05 / One queue, the right hardware

No partition routing. No HPC engineer. No DevOps team.

Genomics, mass-spec, single-cell, and any other omics step all submit to the same Slurm queue. Karpenter provisions the right CPU or GPU family on spot per step — you never write a partition name, and you never hire to keep it running.

06 / Containerized, pinned, reproducible

Verified containers — add a tool, we build it in days.

Every tool ships as a pinned, version-locked container with GPU tuning where it applies. Need one we don't list — STARsolo, OpenSWATH, a custom Slurm pipeline? Send it over; new workloads onboard in days.

Three ways in

Console, CLI, or REST — same cluster, your call.

Submit from the web console if you'd rather not touch Slurm. SSH in and sbatch if you live in the terminal. Wire the REST API into your orchestrator if you automate everything.

01 / Web console

Cohort dashboard — submit, monitor, review.

Browse the omics template catalog, fill the cohort form, hit submit. Live logs, per-sample cost stamp, run history, QC reports. For scientists who'd rather not write sbatch.

Launch the console →

02 / CLI

sbatch sarek --input cohort.csv

Slurm-native. SSH in and submit the way you would on any HPC system — same sbatch, squeue, sacct, scancel. For bioinformaticians who already live in the terminal.

CLI quickstart →

03 / REST API

POST /v1/jobs/submit

Wire Clusterra into your in-house pipeline, Airflow DAG, or Nextflow Tower. JSON in, JSON out. For platform teams that want Clusterra as the compute backend, not the front door.

API reference →

What you get

A cohort workspace, not just a cluster.

A managed Slurm cluster in your AWS, the full omics suite operated end-to-end, and every cohort's QC and per-sample cost accreting as your program's computational book-of-record.

01 / Cohort workspace

Every run builds your program's provenance record.

Variant call sets, protein quant matrices, QC reports, and per-sample cost stamps accumulate in your own EFS — a cost-stamped record that lives in your account, not ours, and compounds into a system no competitor can pull out of your VPC.

02 / Full omics suite

Genomics to mass-spec — one cluster, one queue.

Any nf-core pipeline public or private (sarek, rnaseq, and the rest), GPU alignment and DeepVariant (Parabricks), DIA quant (AlphaDIA, DIA-NN), search and glyco (MetaMorpheus, Sage), single-cell, and your own custom jobs — the same job queue, Karpenter picks the hardware. No partition routing in your scripts.

03 / Your AWS, your IP

Patient FASTQ, raw MS, and identified variants never leave your VPC.

Patient samples and IP-sensitive cohorts are program IP. They stay in your IAM perimeter — not on our infra, not routed through our control plane. BYOC means you see every dollar on your AWS bill, and your Savings Plans & credits apply.

Benchmarks

Full-pipeline cost on the omics workloads you actually run.

Spot pricing, checkpoint-restart on, us-east-1. Reproducible benchmarks on public datasets (PRIDE, GIAB) — fork the repo, verify the numbers.

Workload
Cost
Reference
AlphaDIA proteomics cohort
timsTOF Ultra 2 · HeLa 200ng · Mann lab library
$0.05 per sample, 13 min wall-clock
8,591 proteins, 105,414 precursors · 50-sample cohort runs in parallel, not serial
Sarek + Parabricks 30× WGS
Parabricks GPU alignment + DeepVariant · g5 spot
$2.59 per sample, 2h 32m
GIAB NA12878 · SNP F1=0.9966 / INDEL F1=0.9934 against hap.py truth set
Glyco-MAPPs Tn-glycopeptide discovery
pGlyco3 / MSFragger-Glyco → Boltz-2 fold · 3 replicates
$0.73 per cohort
PXD050580 COSMC-KO MDA-MB-231 · 12 high-confidence Tn-glycopeptide PSMs, 46 min total
TCR-pMHC ternary complex co-folding
5-chain structure prediction · Boltz-2 · A10G
$0.13 per complex
Reference DockQ 0.59, post-cutoff DockQ 0.62 against published crystals

See all the benchmarks →

How it works

First cohort running in 30 days.

Three steps. All in your AWS account.

01 / Connect

Connect your AWS account — about 10 minutes

BYOC via a cross-account IAM role. Your VPC, your billing, your data. We deploy the Slurm + Karpenter control plane into your account — nothing routes through ours.

02 / Pick a pipeline

Pick an omics template or bring your workflow

nf-core/sarek variant calling, Parabricks GPU alignment, AlphaDIA / DIA-NN cohort, MetaMorpheus glyco, single-cell — or submit your own Slurm or Nextflow job. The cluster knows what hardware each step needs; you never write a partition name.

03 / Submit

Submit — results + provenance back in your EFS

sbatch, REST, or the console. Karpenter provisions the right instance family on spot. Checkpoint-restart on eviction. Live cost meter. Per-sample cost stamp. Reproducibility bundle on every run.

Beyond raw AWS

AWS sells you the parts. We hand you the working instrument.

Batch, PCS, and ParallelCluster are those parts pre-sorted but still un-assembled. We deliver the cluster already built, validated, and running — in your own account.

01 / Day-one cluster

Working on day one — not a kit to assemble.

Batch, PCS, and ParallelCluster are kits: someone still has to design the cluster, build the containers, wire up Slurm, and tune the GPUs before a single cohort runs correctly. That’s a dedicated headcount’s worth of HPC/DevOps work. We hand it to you already built and validated — a managed Slurm cluster running right the day we turn it on.

02 / Survivable spot

Spot GPUs at ~60% off — without the dead runs.

Spot GPU is ~60–70% cheaper than on-demand, but on raw AWS a long-running alignment or DIA cohort dies the instant the instance is reclaimed — so most teams never use it. We catch the 2-minute reclaim warning, drain the job cleanly, and resume it. The cheap compute becomes usable for the long jobs that actually need it.

03 / Costed & reproducible

Every run is costed and reproducible — automatically.

On raw AWS you get one monthly bill and no record of how a result was produced. We stamp every job with its dollar cost as it runs — spend visible per sample, per patient, per project — and capture the exact pinned container digest and script behind each run, so any variant call set or quant matrix can be reproduced or re-run months later without rebuilding the environment.

All of that — the day-one cluster, survivable spot, and costed, reproducible runs — for less than a tenth of the hire it would take to build it yourself:

Pricing

Pick your plan by how much you run.

Every plan is the full platform. Plans differ only by how much management credit is included.

Solo
$99/mo per cluster

For one scientist getting started. Run real campaigns on a proper GPU cluster without committing to anything bigger.

Included credits$99/mo≈ 100 GPU-hrs
Rate$0.40/GPU-hr + $0.04/vCPU-hrmetered from your credit
OverageSame ratepast your included credits

Get started →
Most popular
Team
$499/mo per cluster

For a team running every week. Pay $499, get $999 of management credit — about 2× the value.

Included credits$999/mo≈ 1,000 GPU-hrs
Rate$0.40/GPU-hr + $0.04/vCPU-hrmetered from your credit
OverageSame ratepast your included credits

Get started →
Org
$1,499/mo

For running hard, with zero math. One flat price covers everything you run — it never changes.

Included creditsUnlimitedone flat fee
RateNoneno metering, ever
Overagenothing to meter

Talk to us →

Against any of those, a $99–$1,499/mo management fee is a rounding error — and not a license, a CRO, or a headcount you'd otherwise carry.

Questions, answered

What exactly am I paying Clusterra for?

For running your cluster — the managed software, the validated scientific stack, spot survival, and provenance. That is the only thing you pay us. The compute itself (GPUs, CPUs, storage) is billed separately and directly by AWS in your own account, at AWS prices — we never touch or mark up that bill.

Which plan should I pick, and how does it bill?

One scientist, light or occasional runs → Solo ($99/mo, includes $99 of management credit). Running most weeks → Team, the best value ($499/mo, includes $999 of credit — ~2×). Running hard and want one predictable bill → Org ($1,499/mo flat, unlimited, no metering).

“Management credit” is prepaid Clusterra fee — not compute, and not your AWS credits. Solo and Team meter it at one uniform rate, $0.40/GPU-hr + $0.04/vCPU-hr; once the credit is used up you keep paying that same rate, nothing changes. Hours vary by instance; AWS bills the compute separately and directly, at AWS prices.

Can I use my AWS & NVIDIA credits?

Yes — this is a real advantage of BYOC. Because compute runs in your own account, your AWS Activate and NVIDIA Inception credits pay for it directly. A SaaS platform that bills you cannot apply those credits — they'd expire unused. Many teams run for months on credits alone; the management fee is the only thing you pay us.

What's the pilot?

A free 30-day pilot: we stand up your cluster in your AWS, wire your workflows, and get a real campaign running with you — no charge.

Can I cancel anytime?

Yes — no lock-in. Cancel anytime and changes take effect on your next cycle. Because everything runs in your own AWS account, your data and clusters stay with you.

Start free — no credit card →

Or book a free pilot — we get a real campaign running, no charge.

$ sbatch sarek --input cohort.csv --tools deepvariant # Your AWS, your VPC. Per-sample cost stamped automatically.

Scope a pilot on your cohort.

30 minutes to scope the workflow. Free 30-day pilot with your first genomics or proteomics cohort running in your AWS account — no charge. Then BYOC plans from $99/mo. Three design-partner slots — closes when filled.

Prefer email? hello@clusterra.cloud · or join the community Slack →