Ruben Chazarra-Gil

The paper creates a single-cell atlas of transcript usage changes during antiviral immune responses in humans, showing lineage-specific and ancestry-related variations across influenza and SARS-CoV-2 infections.

This paper investigates how splitting sequencing samples across lanes affects results in bulk and single-cell sequencing, showing reduced detail and potential bias in analyses.

The paper evaluates batch correction methods for single-cell RNA-seq using BatchBench, showing their performance across datasets.