Christoph Hafemeister

This paper introduces a 3D co-culture model of bone sarcoma metastasis in the lung and identifies a contact-dependent epithelial remodeling response with potential therapeutic targets.

This study models EWS::FLI1 fluctuations in Ewing sarcoma, showing that partial depletion promotes metastasis and identifies gene clusters and transcription factors linked to poor prognosis.

The paper evaluates differential expression methods in scRNA-seq, finding pseudo-bulk approaches without prior transformation perform best and recommends using three pseudo-replicates for within-sample comparisons.

This study shows that low-coverage single-cell RNA sequencing of more samples increases statistical power for cell-type-specific eQTL analysis compared to high-coverage sequencing of fewer samples.

The paper predicts cellular positions in the Drosophila embryo using scRNA-seq data by benchmarking methods against spatially annotated genes.

The paper infers bacterial sRNA regulatory networks and integrates them with transcription factor networks, identifying novel sRNA-mRNA interactions in multiple bacterial species.

This paper introduces a normalization method for scRNA-seq data using regularized negative binomial regression to reduce technical variation while preserving biological signals.

Seurat v3 finds scored mutual-nearest-neighbor anchors in canonical correlation space to integrate scRNA-seq batches and transfer labels, protein levels and transcriptome-wide expression across modalities.

The paper uses single-cell RNA-seq to study the development of cortical interneurons, identifying key transcription factors and cell states involved in their diversification.

The paper introduces a method to simultaneously measure epitopes and transcriptomes in single cells using oligonucleotide-labeled antibodies.