Install
openclaw skills install @drdaviddelorenzo/dnaspPopulation genetics of pre-aligned DNA sequences or multi-sample VCFs using selected DnaSP 6 methods. Use for diversity, neutrality statistics, linkage disequilibrium, InDel polymorphism, divergence, MK, Ka/Ks and codon usage; not alignment, phasing or clinical interpretation.
openclaw skills install @drdaviddelorenzo/dnaspFire when a user requests population-genetic analysis of aligned DNA, a supported VCF, or a DnaSP-compatible statistic listed below. Do NOT fire for sequence alignment, read mapping, haplotype phasing, clinical advice or unsupported coalescent significance tests.
Analyse genetic variation in supplied alignments using 16 selected DnaSP methods. This is not a complete replacement for the DnaSP GUI or all its analysis modes. Read the statistical reference for definitions, exclusions, source conventions, file formats, examples and release validation evidence.
Fu and Li D*/F* and outgroup D/F mirror Data > Segregating Sites/Mutations =
Segregating sites, using DnaSP's v5-style panels. The rp49 Eta-setting D*/F*
figures can be reproduced by substituting eta for S, but this is not a general
conversion: FULI.vb also changes singleton and external-mutation capping
(SingleMut and ExternaMut subtraction). No Eta-mode switch is implemented.
dnasp.py from this skill's own directory; it is self-contained (its
reproducibility writers ship beside it as _repro_writers.py). Install matplotlib for figures.--input; for VCF
use --vcf; for two-locus HKA alone use --hka-file --analysis hka.--analysis. Supply --outgroup,
--input2 or --pop-file when needed. Use --genetic-code vertebrate-mitochondrial for the matching mitochondrial table. The default is
standard. Coding intervals must be preselected and divisible by three.--analysis all is opportunistic: inspect its completed/skipped manifest.report.md and reproducibility/manifest.json.
Distinguish a failed analysis, an undefined statistic and an excluded site.commands.sh replays on the recorded host/code path into a new output folder;
moving a run requires the code and dependencies as well as its input archive.python <skill-dir>/dnasp.py --demo --output new_demo_run
python <skill-dir>/dnasp.py --input alignment.fas --analysis polymorphism,ld --output new_run
python <skill-dir>/dnasp.py --input coding.fas --outgroup OutSeq --genetic-code vertebrate-mitochondrial --analysis mk,kaks,codon --output new_coding_run
python <skill-dir>/dnasp.py --vcf samples.vcf --analysis polymorphism,sfs,fufs --output new_vcf_run
<skill-dir> is this skill's own directory: ${HERMES_SKILL_DIR} on Hermes,
{baseDir} on OpenClaw.
The synthetic demo contains 10 ingroup sequences, one outgroup and 300 sites:
| Quantity | Demo value |
|---|---|
| S / haplotypes | 5 / 8 |
| Hd / Tajima D | 0.9556 / 0.6789 |
| MK Pn / Ps / Dn / Ds | 2 / 3 / 2 / 1 |
| MK alpha | 0.6667 |
| Ka / Ks / omega | 0.010239 / 0.030291 / 0.3380 |
| Ts / Tv | 4 / 1 |
The demo runs 15 modules; HKA uses a separate two-locus input. The regression suite, rather than the printed banner alone, checks the expected figures.
output/
report.md
results.tsv # polymorphism and windows
summary.json # module summaries, window midpoints, named ENC/null
result.json # structured envelope: headline summary, summary.json payload, artifacts
ld_pairs.tsv # when LD pairs exist
figures/ # when matplotlib is available
reproducibility/
inputs/
commands.sh
environment.yml
manifest.json
checksums.sha256
Python 3.10 or later. Core estimators and the reproducibility bundle use the
standard library. Plotting uses matplotlib; without it the statistics, report
and TSV files are still written and figures are skipped. Install with
pip install -r requirements.txt or use environment.yml. The Windows
validation runner targets Python 3.12.
All sequence analysis and output remain local. This skill is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.
The agent selects documented inputs/options, executes the skill and explains reported results. The code computes the statistics. Neither the agent nor the skill may fabricate GUI validation, P-values or missing results.
Call dnasp.py directly. Use --analysis for module selection, not invented
flags such as --pi, --kaks or --n-sim. The implemented options include VCF
input, populations and genetic-code selection; --help lists them all.
Use an alignment tool before this skill when sequences are not aligned. A VCF filtering/phasing workflow may prepare input, but every filter and phase choice must be recorded. Downstream reporting may use the Markdown report and available TSV files; the TSV does not contain every module's results.
Recheck source/help-derived regression cases and the 170 historical comparison fixtures after changes to formulas, masks or parsers. Review GUI differences when the target DnaSP build or analysis mode changes. Keep this file, the method reference, CLI metadata, version and catalogue consistent. New Windows GUI observations must be reviewed before changing published concordance counts.