Stephan Beck

GIMMEcpg is a fast, scalable methylation imputation tool that improves accuracy and efficiency over existing methods, with a machine learning variant offering higher accuracy.

This study identifies epigenetic changes and accelerated ageing in multifocal small intestinal neuroendocrine tumours, revealing altered metabolic gene regulation and tumour-specific methylation patterns.

This study investigates whether donor DNA methylation can predict acute graft-versus-host disease (aGVHD) in HCT, finding that a classifier developed from methylation data failed to validate in an independent cohort.

FORGEdb integrates genomic annotations to prioritize functional variants and target genes for complex diseases.

The paper evaluates epigenetic age acceleration in colorectal cancer using open access data and develops a classifier with diagnostic potential based on epigenetic age acceleration.

The paper evaluates nine epigenetic age acceleration scores and their associations with 18 cardio-metabolic phenotypes in an Eastern European cohort, finding sex-specific and counter-intuitive relationships.

The paper benchmarks five DNA methylation platforms and shows imputation improves interoperability between them.

The paper critiques a recent commentary on DNA methylation analysis, highlighting misconceptions in algorithm evaluation and reporting contradictory results on real EWAS datasets.

This paper introduces CAMDAC, a method to deconvolve tumor-normal DNA methylation profiles while accounting for copy number changes, revealing epigenetic instability and distinct patterns in lung cancer.

GenomeChronicler generates genomic reports from whole genome or exome sequencing data, linking variants to known phenotypes using public databases.

The paper develops CellAgeClock, an epigenetic clock to measure ageing in human cells, identifies anti-ageing drugs, and validates their efficacy in vivo.

The paper evaluates existing statistical algorithms for identifying cell-type-specific DNA methylation associations in EWAS and highlights biases in prior comparative studies.

The paper describes the PGP-UK multi-omics reference panel, providing open access to genomic, methylomic, and transcriptomic data with quality control and API access.

The paper identifies 61 novel mutations in the aged human testes, most affecting the RAS-MAPK pathway, showing evidence of selfish selection in the male germline.

PGP-UK explores citizen science in genomics by recruiting participants, sharing data, and developing tools to advance personalized medicine.

This paper introduces CellDMC, a statistical algorithm that identifies differentially methylated cell-types in EWAS, achieving high sensitivity and specificity in detecting methylation changes in smoking-related lung cancer.

This study identifies widespread H3K27ac acetylomic variation in AD cases compared to controls, linking it to disease-related pathways and AD-associated genetic variants.

The paper identifies DNA methylation oscillations as a marker for enhancer classification, showing high predictive power compared to other methods.

This study identifies age-related DNA methylation changes in old Swedish twins over 20 years, showing stability across cohorts and genetic influences independent of age.

The paper identifies a differentially variable DNA methylation signature in rheumatoid arthritis discordant monozygotic twins, suggesting epigenetic variability contributes to autoimmune disease.

The paper identifies a susceptibility variant in CCHCR1 associated with alopecia areata and shows its effect in mice with patched hair loss.

The paper integrates chromatin accessibility and DNA methylation data from human pancreatic islets to refine regulatory mechanisms at Type 2 Diabetes susceptibility loci.

This study compares the epigenomes of neutrophils and monocytes to identify regulatory elements and chromatin states, revealing differences in enhancer activity and DNA methylation.

This paper critiques a study claiming ReFACTor improves EWAS by correcting cell-type heterogeneity, finding its claims lack rigorous statistical support.

This paper compares reference-based deconvolution algorithms for correcting cell-type heterogeneity in EWAS, finding that non-constrained methods like robust partial correlations outperform constrained approaches.

The paper measures and compares transcriptional and epigenetic variability across immune cell types and finds neutrophils exhibit higher variability linked to immune pathways and environmental exposure.