PyStatsGenomic
Genomics and computational-biology statistical computing for Python.
Status:
0.1.0— first module shipped. Hardy–Weinberg equilibrium is available now; more statistical-genetics methods are on the roadmap below.
PyStatsGenomic is part of the open-core PyStatistics family:
| Package | Layer |
|---|---|
pystatistics |
Fundamental, general statistics |
pystatsbio |
Biotech / pharma statistics |
pystatsclinical |
Clinical-trial / clinical-research statistics |
pystatsgenomic |
Genomics / computational-biology statistics |
pystatsfinance |
Financial / quantitative statistics |
pystatsinsurance |
Actuarial / insurance statistics |
Like its siblings, it builds on pystatistics for the general statistical layer
and adds methods specific to genomics.
What's available now (0.1.0)
Hardy–Weinberg equilibrium for a biallelic locus, via the exact test (Wigginton, Cui & Abecasis 2005, the default) or the Pearson chi-square test:
from pystatsgenomic import hwe
result = hwe.hardy_weinberg(n_AA=298, n_Aa=489, n_aa=213)
print(result.summary())
# Allele frequencies on their own:
freqs = hwe.allele_frequencies(n_AA=298, n_Aa=489, n_aa=213)
hardy_weinberg reports allele frequencies, expected genotype counts, the
chi-square statistic, and the p-value (1 df — HWE estimates an allele
frequency). It fails loud on negative/non-integer counts and an empty sample.
Roadmap (candidates, not commitments)
- Linkage disequilibrium (D, D′, r²) and genotyping QC metrics.
- Single-locus association and GWAS-scan orchestration (with genomic control).
- Population-genetics summaries: Fst, nucleotide diversity, Tajima's D.
Installation
pip install pystatsgenomic
License
MIT © Hai-Shuo. Part of the SGCX open-core ecosystem.
Metadata
Release files for pystatsgenomic 0.1.1
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