Marc‐Phillip Hitz

hvantk is a framework for variant annotation and analysis that integrates multi-omic data, improving the recovery of disease genes in case-control cohorts.

This study uses single-cell RNA-seq to analyze transcriptional changes in mouse hearts during perinatal development, identifying gene regulatory patterns and a cell type-independent imprinted gene signature.

The paper identifies TAK1's role in heart development through genetic analysis and shows its activation at the primary cilium via TGFB/BMP signaling.

This study identifies rare variants and digenic interactions associated with congenital heart disease using a large-scale exome case-control analysis.

ibaqpy computes iBAQ values for proteomics data using SDRF metadata, improving scalability and reproducibility in large-scale experiments.

The paper develops a heart-specific model to predict splice-disrupting variants in childhood heart disease, identifying variants missed by existing tools and showing higher accuracy in cardiac genes.

The paper introduces the OmicsDI REST interface for programmatic access to omics datasets and provides R and Python libraries for interacting with the API.

The paper identifies calcium signalling defects as a novel cause of congenital heart disease through whole exome sequencing and functional validation in zebrafish.

The paper develops an efficient feature selection workflow and R package for high-dimensional omics data, evaluated on proteomics and gene expression datasets.