Genomics & Bioinformatics with Sounio
Sounio supports genomics pipelines where measurement uncertainty and provenance matter as much as raw throughput.
Why it fits this domain
- Sequencing and quantification steps carry confidence intervals that should not be dropped.
- Pipelines combine GPU-heavy kernels with strict reproducibility requirements.
- Regulatory and clinical contexts need traceable computational artifacts.
Example workflow outline
fn main() with IO, GPU {
let reads = load_fastq("sample.fastq")
let aligned = align_gpu(reads, "reference.fa")
let variants = call_variants(aligned)
report(variants.with_uncertainty())
}Typical applications
- Differential expression with uncertainty-aware fold-change estimates
- Variant prioritization using confidence-gated filters
- Pathway enrichment with propagated measurement error
