Full GRCh38 in 25 min. Chr22 in 58 s. On a $140 Walmart Chromebook. Your move, Broad Institute.
| Use Case | SeqSwift Time | Industry Standard | ONT Ecosystem Benefit |
|---|---|---|---|
| E. coli AMR (103 MinION Fastq files) | 2.48 seconds | 24–72 hours | Real-time sepsis decisions at bedside |
| MinION FASTQ (Torpedo, 22 files) | 1.4 seconds | Hours (Clair3) | Proven Dorado → SeqSwift integration |
| HPV16/18 Oncology | 0.007 seconds | 4–8 hours | Instant cervical cancer screening |
| Sickle Cell HBB (single) | 0.041 seconds | 45–90 minutes | Bedside diagnosis |
| Sickle Cell HBB (1,000 patients) | 2 seconds | 24–48 hours | Population-scale NICU screening |
| Clinical BAL → AMR | 58 seconds | Days | Outbreak response, field deployment |
| GRCh38 Index Build | 25 minutes | Days on cluster | Offline setup, no cloud dependency |
All benchmarks validated on Walmart Chromebook — Sub-second Diagnostics, Offline, Decentralized — Everywhere
Full GRCh38 genome → 739 MB 2-bit index built in 25 min on $140 Chromebook
| Pilot | Target | Performance |
|---|---|---|
| NK Cell Attenuation + MHC-I Downregulation | Full Genome Immune Evasion Panel | 0.042 s |
| GRCh38 | Full Human Genome (3.1B bases) | 25 min build / 58s chr22 |
| E. coli | Complete Genome (4.6 Mbp) | 0.016 seconds |
| E. coli AMR | AMR Detection + Clinical Insight (103 real MinION FASTQ files) | 2.48 s |
| HPV16 | Single Oncology Panel | 0.004 seconds |
| HPV16+18 | Combined Panel (3.45M mutations) | 0.0007s |
| SARS-CoV-2 | Variants Analysis | 0.008 seconds |
| VHL | Hereditary Cancer Panel | 0.006 seconds |
Genome Size: 3.1B bases
Variants: 50M
RAM Peak: 489 MB
SHA256:
47f3e04c9c6195dea32e2652db7599fb28078c5229dcc4e15d32d216aad7e1ae
Size: 3.1B bases → 739 MB 2-bit index
Platform: Chromebook (Crostini Linux)
Use Case: Clinical diagnostics, research genomics
Hardware: Verified on $140 Chromebook
Input: 103 real MinION FASTQ files
Detection: gyrA S83L — 55% file-level match rate
Clinical Output: Prescribe aminoglycoside recommendation
Resistance: Fluoroquinolone markers (gyrA, parC)
Use Case: Clinical diagnostics, outbreak surveillance
Hardware: Verified on $140 Chromebook
Genome Size: 4.6 Mbp
Analysis Time: 16 milliseconds
Use Case: Microbial genomics, AMR research
Applications: Outbreak tracking, strain identification
Target: HPV16 genome
Analysis Time: 4 milliseconds
Use Case: Cancer diagnostics, HPV screening
Clinical Impact: Point-of-care screening
Throughput: 3.45M mutations analyzed
Analysis Time: 7 milliseconds
Use Case: Comprehensive HPV screening
Coverage: 70% of cervical cancer cases
Target: HBB gene locus (337 pathogenic variants)
Single Mode: 41 milliseconds per patient
Batch Mode: 1,000 patient cohort ~ 2 seconds
Use Cases: Bedside triage, population screening
Target: SARS-CoV-2 genome & variants
Analysis Time: 8 milliseconds
Use Case: Pandemic surveillance, variant tracking
Applications: Real-time outbreak monitoring
Target: VHL gene locus
Analysis Time: 6 milliseconds
Use Case: Hereditary cancer screening
Risk Assessment: Family screening programs
Click on any pilot's download button above or visit the v1.13 release page directly.
Email david@seqswift.com with:
Why we ask: We're learning from early users to align future development. Your feedback directly shapes the roadmap.
# Example decryption (passphrase provided via email)
gpg --decrypt SeqSwift_GRCh38_BOOM_v1.13.zip.gpg > SeqSwift_GRCh38_BOOM_v1.13.zip
unzip SeqSwift_GRCh38_BOOM_v1.13.zip
cd SeqSwift_GRCh38_BOOM_v1.13
./seqswift --help
Evaluating genomic analysis tools for academic or clinical research projects.
Exploring diagnostic workflows and precision medicine applications.
Benchmarking performance against existing genomic pipelines.
Teaching computational genomics and bioinformatics courses.
Building on genomic infrastructure and creating new analysis tools.
Resource-limited settings needing accessible genomic analysis.
Free pilot access in exchange for testimonial/feedback. Help shape the future of genomic analysis.
3 lifetime licenses randomly awarded weekly to users who provide feedback on their experience.
Educational licenses available on request for teaching and non-commercial research.
Input:
Only 12 decryption passphrases will be issued in 2025.
This scarcity protects our patent-pending technology while we finalize commercial licensing.
Ready to evaluate SeqSwift?
Email MeA fourth-year international medical graduate completing clinical training in the United States. Self-taught in systems programming (MIT 6.001 via MITx), with prior contributions to the Journal of Visualized Experiments (JoVE) and technology analysis at Forrester Research in Cambridge. Moved to Atlanta in 2024 to build sub-second, bedside-ready sequencing that runs on a $140 edge device — in a Level-I trauma bay or a rural Kenyan ward.
A medical resident at UNC Greenville bringing clinical validation expertise and a global health perspective forged through UN experience. Bridges the gap between cutting-edge genomic technology and real-world deployment in resource-limited settings across Sub-Saharan Africa and beyond.
During a recent family-medicine clerkship, the young daughter of his preceptor – a little girl he and the team cared for together in clinic – died of an overwhelming infection that rapid diagnostics might have caught sooner. At the same time, several close friends and former colleagues from Kenya lost patients and family members to late-diagnosed sepsis and resistant pathogens.
Those two losses made the mission personal: no child, anywhere, should die because a genomic result took days instead of seconds.
No big lab. No big budget.
Just code that refuses to let the next child wait.
Website: seqswift.com
Main Repo: SeqSwift-LiteSpeed
X/Twitter: @schlayguy
Contact: david@seqswift.com