blup

A chronological age predictor based on DNA methylation

This Repository contains materials to learn mixed models, dissect it to extract BLUEs and BLUPs

A genome-wide association study (GWAS) tool written in R

An R packages for Genomics, quantGen, and popGen studies, especially for crop species.

A comparison of classical and machine learning-based phenotype prediction methods on simulated data and three plant species

The HAPPI_GWAS_2 is a pipeline built for genome-wide association study (GWAS).

UAI-TREM: Unravelling Additive and Indirect genetic effects with Time-dependent Random Effect Models. An R engine for genetic evaluation by AI-REML and Gibbs: breeding values, single-step genomics (ssGBLUP, APY), reaction norms and multi-trait models, in C++ with no run-time dependency.

General-purpose linear mixed model solver

The project focused on the analysis of foxes from 3 different farms and the subsequent presentation of trait heritability results, genetic trends, breeding values and relationship matrix.

Solves kernel ridge regression within the the mixed model framework. All the estimated components and parameters, e.g. BLUP of dual variables and BLUP of random predictor effects for the linear kernel (also known as RR-BLUP), are available.

Analysis code and phenotypic data for a multi-trait plant-architecture ideotype in soybean, Russian Far East

Анализ генетических данных в R с использованием BLUP. Смешанные линейные модели, подготовка данных и оценка генетической ценности

Plant-breeding analytics: mixed-model BLUPs, genomic prediction, combining ability & cross planning — with a grounded assistant that explains results only from verified computation. TypeScript orchestrator + R compute kernel.

Scripts and spreadsheets for performing single-variate Best Linear Unbiased Predictor (BLUP) to find beef cattle breeding values #KeepEPDsReal

Your one-stop solution for comprehensive genotype × environment interaction and stability analysis (WAASB model) using the metan package. Save time, perform analyses for all traits at once, and gain insightful visualizations effortlessly!"