Jan Graffelman

The paper extends Aitchison's logratio analysis to multiallelic polymorphisms, showing how Hardy-Weinberg equilibrium manifests in genotypic compositions and introducing a measure for disequilibrium.

This paper proposes a constrained least squares method to estimate Jacquard's genetic identity coefficients and related parameters, showing computational efficiency comparable to maximum likelihood methods.

The paper demonstrates the transitivity of the Hardy-Weinberg law for multi-allelic polymorphisms and shows its application in genetic data analysis and testing for equilibrium.

The paper describes a system for harmonizing phenotype data across multiple studies in the TOPMed program, enabling reproducible and shared phenotype data for over 80 studies.

The paper introduces a network algorithm for exact Hardy-Weinberg equilibrium testing on X chromosomal variants with multiple alleles, significantly reducing computation time for up to five alleles.

The paper improves MDS goodness-of-fit calculations by introducing new statistics to filter poorly represented observations in large datasets.

This study evaluates using RNA-seq data to detect kinship by estimating pairwise identity-by-descent, showing it can identify up to second-degree relationships with low to moderate sequencing depth.

The paper develops a compositional canonical correlation analysis method called CODA-CCO to study relationships between two compositions, using geological data to illustrate its application.

This paper introduces a method combining genetic bootstrapping, multidimensional scaling, and discriminant analysis to classify genetic relationships with high accuracy using identity-by-state data.

The paper extends exact tests for Hardy-Weinberg equilibrium to multi-allelic variants, accounting for gender differences in X-chromosomal and autosomal data.