Biology subjects

Graffelman, J.

Publications and source records attributed to Graffelman, J..

11 recordsLinked to original sources

bioRxiv2025

A logratio approach to the analysis of autosomal genotype frequencies across multiple samples

John Aitchison has shown that the logratio principal component analysis of multiple samples of a biallelic polymorphism can evidentiate the Hardy-Weinberg law. This article extends Aitchisons work to multiallelic polymorphisms showing how the Hardy-Weinberg law manifests itself in a logratio based statistical analysis of larger genotypic compositions. Some fundamental relationships between allelic and genotypic compositions are derived, and the close relationships between the logratio principal component analysis of allelic and genotypic compositions and the corresponding compositional biplots are established. We perform simulations and practical genetic data analysis to explore the implications of Hardy-Weinberg equilibrium for the logratio principal component analysis of genotypic compositions. A general multiallelic compositional measure for disequilibrium is presented, and shown to relate to the classical inbreeding coefficient. The proposed compositional analysis is illustrated with biallelic glyoxalase genotypes and multiallelic forensic STRs from the 1,000 Genomes project.

genetics↗

bioRxiv2024

Estimation of Jacquard's genetic identity coefficients with bi-allelic variants by constrained least-squares

The Jacquard genetic identity coefficients are of fundamental importance in relatedness research. We address the estimation of these coefficients as well as other relatedness parameters that derive from them such as kinship and inbreeding coefficients using a concise matrix framework. Estimation of the Jacquard coefficients via likelihood methods and the expectation-maximization algorithm is computationally very demanding for large numbers of polymorphisms. We propose a constrained least squares approach to estimate the Jacquard coefficients. A simulation study shows constrained least squares achieves root-mean-squared errors that are comparable with those of the maximum likelihood approach, in particular when founder allele frequencies are unknown, while obtaining enormous computational savings.

genetics↗

bioRxiv2021

The transitivity of the Hardy-Weinberg law

The reduction of multi-allelic polymorphisms to variants with fewer alleles, two in the limit, is addressed. The Hardy-Weinberg law is shown to be transitive in the sense that a multi-allelic polymorphism that is in equilibrium will retain its equilibrium status if any allele together with its corresponding genotypes is deleted from the population. Similarly, the transitivity principle also applies if alleles are joined, which leads to the summation of allele frequencies and their corresponding genotype frequencies. These basic polymorphism properties are intuitive, but they have apparently not been formalized or investigated. This article provides a straightforward proof of the transitivity principle, and its usefulness in practical genetic data analysis with multi-allelic markers is explored. In general, results of statistical tests for Hardy-Weinberg equilibrium obtained with polymorphisms that are reduced by deletion or joining of alleles are seen to be consistent with the formulated transitivity principle. We also show how the transitivity principle allows one to identify equilibrium-offending alleles, and how it can provide clues to genotyping problems and evolutionary changes. For microsatellites, which are widely used in forensics, the transitivity principle implies one expects similar results for statistical tests that use length-based and sequence-based alleles. High-quality autosomal microsatellite databases of the US National Institute of Standards and Technology are used to illustrate the use of the transitivity principle in testing both length-based and sequence-based microsatellites for Hardy-Weinberg proportions. Test results for Hardy-Weinberg proportions for the two types of microsatellites are seen to be largely consistent and can detect allele imbalance.

genetics↗

bioRxiv2021

Maximum likelihood estimation of the geometric niche preemption model

The geometric series or niche preemption model is an elementary ecological model in biodiversity studies. The preemption parameter of this model is usually estimated by regression or iteratively by using Mays equation. This article proposes a maximum likelihood estimator for the niche preemption model, assuming a known number of species and multinomial sampling. A simulation study shows that the maximum likelihood estimator outperforms the classical estimators in this context in terms of bias and precision. We obtain the distribution of the maximum likelihood estimator and use it to obtain confidence intervals for the preemption parameter and to develop a preemption t test that can address the hypothesis of equal geometric decay in two samples. We illustrate the use of the new estimator with some empirical data sets taken from the literature and provide software for its use.

ecology↗

bioRxiv2020

A network algorithm for the X chromosomal exact test for Hardy-Weinberg equilibrium with multiple alleles

Statistical methodology for testing Hardy-Weinberg equilibrium at X chromosomal variants has recently experienced considerable development. Up to a few years ago, testing X chromosomal variants for equilibrium was basically done by applying autosomal test procedures to females only. At present, male alleles can be taken into account in asymptotic and exact test procedures for both the bi- and multiallelic case. However, current X chromosomal exact procedures for multiple alleles rely on a classical full enumeration algorithm and are computationally expensive, and in practice not feasible for more than three alleles. In this article we extend the autosomal network algorithm for exact Hardy-Weinberg testing with multiple alleles to the X chromosome, achieving considerable reduction in computation times for multiallelic variants with up to five alleles. The performance of the X-chromosomal network algorithm is assessed in a simulation study. Beyond four alleles, a permutation test is, in general, the more feasible approach. A detailed description of the algorithm is given and examples of X chromosomal indels and microsatellites are discussed.

genetics↗

bioRxiv2020

A system for phenotype harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institutes Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 TOPMed studies per phenotype. We discuss the challenges faced in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

genetics↗

bioRxiv2019

Goodness-of-fit filtering in classical metric multidimensional scaling with large datasets

Metric multidimensional scaling (MDS) is a widely used multivariate method with applications in almost all scientific disciplines. Eigenvalues obtained in the analysis are usually reported in order to calculate the over-all goodness-of-fit of the distance matrix. In this paper, we refine MDS goodness-of-fit calculations, proposing additional point and pairwise good-ness-of-fit statistics that can be used to filter poorly represented observations in MDS maps. The proposed statistics are especially relevant for large data sets that contain outliers, with typically many poorly fitted observations, and are helpful for improving MDS output and emphasising the most important features of the dataset. Several goodness-of-fit statistics are considered, and both Euclidean and non-Euclidean distance matrices are considered. Some examples with data from demographic, genetic and geographic studies are shown.

genetics↗

bioRxiv2019

Assessment of kinship detection using RNA-seq data

Analysis of RNA sequencing (RNA-seq) data from related individuals is widely used in clinical and molecular genetics studies. Sample labelling mistakes are estimated to affect more than 4% of published samples. Therefore, as a method of data quality control, a way to reconstruct pedigrees from RNA-seq data would be useful for confirming the expected relationships. Currently, reconstruction of pedigrees is based mainly on SNPs or microsatellites, obtained from genotyping arrays, whole genome sequencing and whole exome sequencing. Potential problems with using RNA-seq data for kinship detection are the low proportion of the genome that it covers, the highly skewed coverage of exons of different genes depending on expression level and allele-specific expression. In this study we assess the use of RNA-seq data to detect kinship between individuals, through pairwise identity-by-descent (IBD) estimates. First, we obtained high quality SNPs after successive filters to minimize the effects due to allelic imbalance as well as errors in sequencing, mapping and genotyping. Then, we used these SNPs to calculate pairwise IBD estimates. By analysing both real and simulated RNA-seq data we show that it is possible to identify up to second degree relationships using RNA-seq data of even low to moderate sequencing depth.

genomics↗

bioRxiv2018

Multidimensional Scaling and Relatedness Research

Multidimensional scaling is a well-known multivariate technique, that is often used in genetics for studying population substructure. In this paper we show that multidimensional scaling of marker data is of relevance for relatedness research. Relatedness is usually investigated by estimating and plotting identity-by-state and identity-by-descent allele-sharing statistics. We show that outlying individuals in a map obtained by multidimensional scaling of genetic variables do not necessarily stem from a different human population, but can be the consequence of relatedness. We propose a method for classifying pairs of individuals into the standard relationship categories that combines genetic bootstrapping, multidimensional scaling and discriminant analysis. We validate our method with simulation studies. Given the variant filtering procedures, our method classifies relationships up to and including the fourth degree with high accuracy (96-97%), using only identity by state. The usefulness of the method is illustrated with data from the 1,000 genomes and the GCAT projects.

genetics↗

bioRxiv2017

Multi-allelic Exact tests for Hardy-Weinberg equilibrium that account for gender

Statistical tests for Hardy-Weinberg equilibrium are important elementary tools in genetic data analysis. X-chromosomal variants have long been tested by applying autosomal test procedures to females only, and gender is usually not considered when testing autosomal variants for equilibrium. Recently, we proposed specific X-chromosomal exact test procedures for bi-allelic variants that include the hemizygous males, as well as autosomal tests that consider gender. In this paper we present the extension of the previous work for variants with multiple alleles. A full enumeration algorithm is used for the exact calculations of tri-allelic variants. For variants with many alternate alleles we use a permutation test. Some empirical examples with data from the 1000 genomes project are discussed.

genetics↗

bioRxiv2017

Compositional Canonical Correlation Analysis

The study of the relationships between two compositions by means of canonical correlation analysis is addressed A coimnositional version of canonical correlation analysis is developed. and called CODA-CCO. We consider two approaches, using the centred log-ratio transformation and the calculation of all possible pairwise log-ratios within sets. The relationships between both approaches are pointed out, and their merits are discussed. The related covariance matrices are structurally singular, and this is efficiently dealt with by using generalized inverses. We develop compositional canonical biplots and detail their properties. The canonical biplots are shown to be powerful tools for discovering the most salient relationships between two compositions. Some guidelines for compositional canonical biplots construction are discussed. A geological data set with X-ray fluorescence spectrometry measurements on major oxides and trace elements is used to illustrate the proposed method. The relationships between an analysis based on centred log-ratios and on isometric log-ratios are also shown.

bioinformatics↗