examples

Example data

Small, self-contained datasets so you can run eskaks immediately. They are used in the getting-started tutorial.

genes.fasta for eskaks fasta (dN/dS)

Six codon-aligned versions of one gene (180 bp) from six strains. All 15 pairs come out well under purifying selection (dN/dS ≈ 0.08–0.34, i.e. always < 1).

eskaks fasta examples/genes.fasta -o first_run

lineages.fasta for grouped eskaks fasta (--lineage / --group-average)

The same 180 bp gene from six isolates, but named by lineage: Lineage2, Lineage4, and Bovis, two isolates each. Isolates within a lineage share a block of substitutions, so they cluster. Use it to compare groups instead of individual pairs:

# mean dN/dS between every pair of lineages (and within each)
eskaks fasta examples/lineages.fasta -o lin --group-average

# group by the first letter of the ID instead of splitting on '_':
# Lineage2 + Lineage4 merge into "L", Bovis stays "B"
eskaks fasta examples/lineages.fasta -o lin_fl --group-average --first-letter-lineage

toy_genome/ for eskaks vcf (pN/pS)

A miniature genome (12 genes) with the three inputs eskaks vcf needs, plus a divergence table for the report's reconciliation panel:

File	What it is
reference.fasta	the genome sequence (contig chr1)
genes.gff3	gene annotation (CDS features)
variants.vcf	the SNPs, with AF and DP in the INFO field
variants_mixed.vcf	12 gene01 SNPs with a mix of PASS and LowQual FILTERs, to try --pass-only
variants_multisample.vcf	the same SNPs with genotypes for 20 samples (S01..S20), for --diversity and anything needing per-sample carriers
samples.nwk	a Newick tree over those 20 samples, for --tree (independent-origin counting)
divergence.tsv	a per-gene dN/dS table (gene <TAB> dN/dS)

eskaks vcf \
  --ref examples/toy_genome/reference.fasta \
  --gff examples/toy_genome/genes.gff3 \
  --vcf examples/toy_genome/variants.vcf \
  --genetic-code 11 --report --plot \
  --divergence examples/toy_genome/divergence.tsv \
  -o toy_scan
# then open toy_scan_report.html in a browser

These are synthetic datasets built only to demonstrate the tool; the numbers are not biologically meaningful. Two genes are named PPE_toy1 / PE_PGRS_toy2 to show how repetitive genes are flagged.