Keegan D. Korthauer

Berkson's Paradox: A Common Statistical Error in Genomics Analyses

The paper identifies Berkson's paradox as a common statistical error in genomics analyses and provides examples and approaches to avoid misinterpreting spurious correlations.

decemedip: hierarchical Bayesian modeling for cell type deconvolution of immunoprecipitation-based DNA methylomes

The paper introduces decemedip, a Bayesian hierarchical model for cell type deconvolution of MeDIP-seq data, showing its accuracy and utility in identifying methylation signatures.

RAMEN: Dissecting individual, additive and interactive gene-environment contributions to DNA methylome variability in cord blood

RAMEN dissects gene-environment contributions to DNA methylome variability in cord blood, finding genetics explains the largest proportion of DNAme variance.

Low oxygen promotes extravillous trophoblast progenitor expansion but restrains maturation

The paper shows low oxygen promotes EVT progenitor expansion but restricts their maturation, with HIF-1 playing a partial role in the maturation block.

Accounting for differences between Infinium MethylationEPIC v2 and v1 in DNA methylation-based tools

This study examines differences between Infinium MethylationEPIC v1 and v2, showing high array-level concordance but probe-level variation, and recommends accounting for version differences in analyses.

Distinct Co-Methylation Patterns in African and European Populations and Their Genetic Associations

The paper identifies population-specific DNA methylation patterns in African and European populations and links them to genetic variants and disease-related genes.

Genetic Basis, Quantitative Nature, and Functional Relevance of Evolutionarily Conserved DNA Methylation

The paper identifies evolutionarily conserved DNA methylation sites in great apes and shows their association with cancer but not other diseases.

Complete Reference Genome and Pangenome Expand Biologically Relevant Information for Genome-Wide DNA Methylation Analysis Using Short-Read Sequencing and Array Data

This study shows that using updated reference genomes like T2T-CHM13 and pangenomes increases CpG detection in DNA methylation analysis and improves probe specificity in arrays, leading to more accurate findings in cancer studies.

vmrseq: Probabilistic Modeling of Single-cell Methylation Heterogeneity

vmrseq detects variably methylated regions in single-cell DNA methylation data with improved accuracy and highlights methylation-gene expression correlations.

Conservation and divergence of canonical and non-canonical imprinting in murids

The paper identifies imprinted genes in rat tissues, finds conservation of canonical imprints in embryos but divergence in extra-embryonic tissues, and discovers novel non-canonical imprints.

A Compositional Model To Assess Expression Changes From Single-Cell RNA-Seq Data

The paper introduces an empirical Bayesian mixture model to detect distributional expression changes in single-cell RNA-seq data, showing improved sensitivity over standard approaches.

A practical guide to methods controlling false discoveries in computational biology

This paper benchmarks classic and modern false discovery rate methods in computational biology, finding modern methods with informative covariates offer modest power gains without sacrificing FDR control.

Genome-wide repressive capacity of promoter DNA methylation is revealed through epigenomic manipulation

The paper reanalyzes data showing that forced DNA methylation of promoters strongly represses gene expression and reduces active transcription marks.

Detection and accurate False Discovery Rate control of differentially methylated regions from Whole Genome Bisulfite Sequencing

The paper introduces a method to detect differentially methylated regions from whole genome bisulfite sequencing data while accurately controlling the False Discovery Rate.

High-throughput identification of RNA nuclear enrichment sequences

The paper identifies RNA sequences responsible for nuclear enrichment in lncRNAs using a modified MPRA approach and validates findings with smRNA-FISH.

scDD: A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

scDD identifies differential expression patterns in single-cell RNA-seq by modeling complex distribution differences, outperforming existing methods in detecting subtle gene expression changes.