Swiftomics — pathogen profiling in your browser

What is Swiftomics, and how does it work?

Swiftomics is a zero-install pathogen profiling platform that runs locally in your browser. Point it at Illumina or Nanopore FASTQ reads and it reports acquired AMR genes and virulence factors with identity, coverage, depth, and — for ResFinder hits — antibiotic class and predicted phenotype.

No read data leaves your machine. The only network traffic after page load is fetching a database index on first use, which is then cached locally in IndexedDB.

Alignment is done by KMA and fastq-interleave, compiled to WebAssembly. Reads are streamed from disk into the browser's in-memory filesystem, aligned there, and rendered in the page.

As a result, there are no installs, no command line, no accounts, no data-transfer agreements — useful when reads are clinical, sensitive, or just too tedious to ship to a remote server.

Workflow

Select read type — Illumina paired/single-end or Nanopore.
Provide FASTQ input (separate slots for R1 / R2 in paired mode).
Choose a reference database; set identity and coverage thresholds.
Run alignment and inspect the results table or download all output files.

Databases

ResFinder 2.6.0: Acquired AMR genes (CGE).
CARD 4.0.1: Comprehensive Antibiotic Resistance Database, protein homolog models.
VFDB: Virulence Factor Database — Set A (core) and Set B (full).

Databases load on demand the first time you select them, then cache locally via IndexedDB for instant reuse.

Notes

Defaults of 80% identity and 80% coverage follow common AMR reporting thresholds.
Lower the identity threshold to recover divergent variants; lower the coverage threshold for fragmented or low-depth samples.
Nanopore mode enables KMA's -bcNano for indel-aware base calling.
Output bundle includes .res, .aln, .fsa, .frag.gz, and .mapstat.

Citation

Short communication in preparation. Please cite KMA in the meantime:

Clausen PTLC, Aarestrup FM, Lund O. Rapid and precise alignment of raw reads against redundant databases with KMA. BMC Bioinformatics. 2018;19:307. doi:10.1186/s12859-018-2336-6

Choose input type

Forward reads (R1)

No file

Reverse reads (R2)

No file

Choose database:

Min identity 80%

Min coverage 80%

Terminal