Andrew Butler

This study reports neutralization titers from 355 human sera against 148 influenza strains, showing reduced neutralization of new H3N2 and H1N1 variants.

geneBasis selects an optimal gene panel from scRNA-seq data by iteratively adding genes that maximize manifold distance, outperforming existing methods in resolving cell types and states.

Weighted-nearest neighbor (WNN) analysis in Seurat v4 learns per-cell modality weights to define cell states, enabling a 228-antibody human PBMC CITE-seq reference for RNA-only query mapping.

The paper uses multi-modal single-cell screens to identify regulators of PD-L1 expression and develops a computational framework to improve analysis of perturbation data.

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.

Seurat combines canonical correlation analysis and dynamic time warping to co-embed scRNA-seq datasets from different conditions, platforms, or species, outscoring ComBat and limma in alignment score.

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 develops a low-cost microfluidic instrument for scRNA-seq and applies it to profile synovial tissue from a rheumatoid arthritis patient, identifying 16 transcriptomic clusters and fibroblast subpopulations.