Ludwig Geistlinger

scDiagnostics assesses cell type annotations in single-cell transcriptomics data to detect misleading or conflicting labels that affect downstream analysis.

This paper creates a gut transcriptomics atlas using MERFISH to show how microbiota influences cell types, spatial organization, and molecular responses in the murine gut.

The paper uses spatial transcriptomics to map cell types and their spatial organization in healthy and fibrotic human liver, identifying changes in hepatocyte populations during fibrosis.

The paper uses spatial transcriptomics to study complement system development in the brain, revealing distinct roles of the classical and alternative pathways.

The paper provides a Bioconductor package with curated landmark datasets for single-cell multimodal data, enabling easy access and analysis of seven different technologies.

This study shows thyroid hormone remodels cortical circuits in adult mice, linking metabolic state to exploratory behavior through transcriptional changes in neurons and glia.

The paper describes AnVIL, a cloud-based platform that enables genomic data analysis without data transfer, improving security, scalability, and collaboration.

GenomicSuperSignature compares new RNA-seq datasets to public archives for rapid interpretation using precomputed axes of variation.

SIMON is an open-source platform that enables biomedical researchers to apply machine learning algorithms to high-dimensional data without requiring advanced programming skills.

The paper introduces STORMS, a reporting guideline for human microbiome studies, providing a 17-item checklist to standardize and improve the organization and reporting of microbiome research.

The paper presents a workflow for allele-specific CNA analysis and SNV classification from tumor-only WES data, showing high concordance with gold standard methods.

This paper provides an overview of single-cell RNA sequencing analysis using Bioconductor, highlighting its tools and methods for handling high-dimensional data.

The paper benchmarks gene set enrichment methods using a curated compendium of disease datasets, identifying performance differences and providing recommendations for improved analysis.

HMP16SData provides integrated 16S rRNA sequencing data from the Human Microbiome Project, enabling easier analysis for researchers with basic R skills.

The paper curates a list of 865 bovine transcription factors and analyzes their domain families, conservation, and tissue-specific expression.