PyAGH

PyAGH constructs additive and genomic kinship matrices from pedigree, genotype, transcriptome abundance, and microbiome data, including dominant and epistatic effects, to support genetic association and prediction analyses.

Key Features:

• Versatile Kinship Matrix Construction: Constructs conventional additive kinship matrices from pedigree, genotypes, transcriptome abundance, and microbiome data.
• Advanced Methodologies: Implements genomic kinship matrix construction in combined populations and accommodates dominant and epistatic effects within kinship matrices.
• Pedigree Management: Performs pedigree selection, tracing, and detection and supports pedigree visualization.
• Data Visualization: Visualizes clusters, heatmaps, and Principal Component Analysis (PCA) results derived from kinship matrices.

Scientific Applications:

• Association Studies: Uses kinship matrices from omic datasets to control relatedness and structure in association analyses.
• Prediction Models: Supports genomic prediction models that rely on kinship information derived from pedigree, genotypes, transcriptome abundance, and microbiome data.

Methodology:

Computational methods include construction of additive and genomic kinship matrices, inclusion of dominant and epistatic effects, pedigree selection/tracing/detection and visualization, and visualization of clusters, heatmaps, and PCA based on kinship matrices.