Associate Professor in Statistical and Complex Trait Genetics
I am an Associate Professor, and research group leader, at the Genomic Medicine research group at the Department of Health Science and Technology, Aalborg University, Denmark, and hold a part-time position as clinical academic in theoretical genetics at the Department of Clinical Genetics, Aalborg Univeristy Hospital.
Research
My full publication record can be found at the Publications-page at the top on this site, and my university reseach profile can be found here.
Software Packages
R qgg
The qgg package is a comprehensive tool for large-scale genetic data analysis, built on the idea that certain genomic regions may be enriched for causal variants. It offers efficient infrastructure for linear mixed models, genomic prediction, heritability estimation, and gene set enrichment analysis. qgg supports high-performance computing with multi-core processing, optimized matrix operations, and memory-efficient genotype handling. It includes advanced genomic feature modeling approaches such as GFBLUP and marker set tests to improve discovery and prediction of trait-associated genomic regions.
Please cite
Rohde PD, Sørensen IF and Sørensen P. (2020). qgg: an R package for large-scale quantitative genetic analyses. Bioinformatics 36, 2614-2615 [link]
Rohde PD, Sørensen IF and Sørensen P (2023). Expanded utility of the R package, qgg, with applications within genomic medicine. Bioinformatics 39, btad656 [link]
R gact
The gact package package provides a framework for building and managing a comprehensive database of genomic associations with complex traits. It supports both infrastructure development and data acquisition, enabling integration of single marker associations with broader biological entities such as genes, proteins, metabolites, and pathways. gact streamlines the processing of GWAS summary statistics and biological databases, facilitates fine-mapping using Bayesian linear regression, and performs advanced gene set enrichment analysis. Its goal is to enhance the biological interpretation of genomic data by uncovering complex trait-related relationships.
With gact you create your own curated GWAS summary statistics database and link it directly to your preferred types of gene annotations. With this repository, you can then perform several novel Bayesian analyses at the level of SNPs (fine mapping), genes (Bayes PoPS), and gene sets (Bayes MAGMA)
Please cite
Sørensen P and Rohde PD (2025). A versatile data repository for GWAS summary statistics-based downstream genomic analysis of human complex traits . doi comming soon
Selected method development publications
Shrestha M, Bai Z, Gholipourshahraki T, Hjelholt A, Kjolby MF, Rohde PD, Sørensen P (2025). Enhanced genetic fine mapping accuracy with Bayesian Linear Regression models in diverse genetic architectures. bioRxiv [link]
Bai Z, Gholipourshahraki T, Shrestha M, Hjelholt A, Hu S, Kjolby MF, Rohde PD, Sørensen P (2024). Evaluation of Bayesian Linear Regression derived gene set test methods. BMC Genomics 25, 1236 [link]
Gholipourshahraki T, Bai Z, Shrestha M, Hjelholt A, Hu S, Kjolby MF, Rohde PD, Sørensen P (2024). Evaluation of Bayesian Linear Regression models for gene set prioritization in complex diseases. PLOS Genetics 11(20), e1011463 [link]
Rohde PD, Sørensen IF and Sørensen P (2023). Expanded utility of the R package, qgg, with applications within genomic medicine. Bioinformatics 39, btad656 [link]
Rohde PD, Nyegaard M, Kjolby MF, Sørensen P (2021). Multi-trait genomic risk stratification for type 2 diabetes. Frontiers in Medicine 8, 711208 [link]
Rohde PD, Sørensen IF and Sørensen P. (2020). qgg: an R package for large-scale quantitative genetic analyses. Bioinformatics 36, 2614-2615 [link]
Sørensen IF, Edwards SM, Rohde PD, Sørensen P (2017). Multiple Trait Covariance Association Test identifies Gene Ontology categories associated with chill coma recovery time in Drosophila melanogaster. Scientific Reports 1(7), 2413 [link]
Rohde PD, Demontis D, Cuyabano BCD, The Genomic Medicine for Schizophrenia Group, Børglum AD, Sørensen P (2016). Covariance Association Test (CVAT) identifies genetic markers associated with schizophrenia in functionally associated biological processes. journal 4(203), 1901-1913 [link]
Statistical Genetic Notes
All statistical genetic notes below are shared under a CC BY 4.0 license.
Mendelian Randomization [link]
Introduction to Quantitative Genetics [link]
Estimating of Genetic Predisposition [link]
Estimating of Genetic Predisposition [link]
Gene-Set Enrichment Analyses [link]
Bayesian Linear Regression Models [link]
Tutorial for constructing polygenic scores (PGS) [link]
Course Work
All teaching materials on this page are shared under a CC BY 4.0 license.