Pepkio HWE Equilibrium Studio
github.com/pepkio/pepkio-hwe-equilibrium-studioEvaluates Hardy-Weinberg equilibrium for diploid loci with two to six alleles using chi-square and Guo-Thompson exact tests, inbreeding coefficient F, and plain-language verdicts from observed genotype counts, allele frequencies, or biallelic disease incidence. A browser calculator provides De Finetti plots, export, and Wright-Fisher simulation under selection, drift, mutation, and migration; a Python library and command-line tool submit the same parameters to the Pepkio Tools API for scripted use. Calculator arithmetic for the API client is hosted remotely; the client transmits genotype or simulation inputs and returns structured results and shareable run identifiers.
Sourced from
- bio.tools — pepkio-hwe-equilibrium-studio
- GitHub — github.com/pepkio/pepkio-hwe-equilibrium-studio
Related resources
Constructs Punnett squares and offspring genotype and phenotype ratios for complete, incomplete, codominant, ABO multiple-allele, and sex-linked Mendelian crosses from parent genotypes, with step-by-step walkthroughs and reduced ratio output. A browser calculator provides live grids, textbook presets, PNG and SVG export, and shareable links; a Python library and command-line tool submit the same parameters to the Pepkio Tools API for scripted use. Calculator arithmetic for the API client is hosted remotely; the client transmits cross inputs and returns structured grids, ratios, walkthroughs, and shareable run identifiers.
First bioinformatics-native AI agent skill library enabling local-first, reproducible genomic and population-genetics research workflows built on OpenClaw (871+ stars, MIT License, 2026)
Using single-cell RNA-Seq expression to visualize CNV in cells.
Probabilistic framework for inferring cell fate decisions and trajectory dynamics from multi-view single-cell data using Markov chains and machine learning, integrating RNA velocity, pseudotime, and metabolic labeling to predict differentiation paths and terminal states (scverse/Theis Lab, 449+ stars, BSD 3-Clause)
Genome-wide association studies (GWAS) are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed an R package SNPRelate to provide a binary format for single-nucleotide polymorphism (SNP) data in GWAS utilizing CoreArray Genomic Data Structure (GDS) data files. The GDS format offers the efficient operations specifically designed for integers with two bits, since a SNP could occupy only two bits. SNPRelate is also designed to accelerate two key computations on SNP data using parallel computing for multi-core symmetric multiprocessing computer architectures: Principal Component Analysis (PCA) and relatedness analysis using Identity-By-Descent measures. The SNP GDS format is also used by the GWASTools package with the support of S4 classes and generic functions. The extended GDS format is implemented in the SeqArray package to support the storage of single nucleotide variations (SNVs), insertion/deletion polymorphism (indel) and structural variation calls in whole-genome and whole-exome variant data.