Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now be …

Single-cell technologies have transformed our understanding of human tissues. Yet, studies
typically capture only a limited number of donors and disagree on cell type definitions. …

As single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed, so have
analysis methods. Many methods have been tested, developed, and validated using …

Long-read technologies are overcoming early limitations in accuracy and throughput, broadening
their application domains in genomics. Dedicated analysis tools that take into account …

Single-cell atlases often include samples that span locations, laboratories and conditions,
leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires …

Clustering techniques are widely used in the analysis of large datasets to group together
samples with similar properties. For example, clustering is often used in the field of single-cell …

As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the
number of tools designed to analyse these data has dramatically increased. Navigating the …

Recent years have seen a revolution in single-cell RNA-sequencing (scRNA-seq) technologies,
datasets, and analysis methods. Since 2016, the scRNA-tools database has cataloged …

The utility of human pluripotent stem cell–derived kidney organoids relies implicitly on the
robustness and transferability of the protocol. Here we analyze the sources of transcriptional …

The increasing generation of population-level single-cell atlases has the potential to link
sample metadata with cellular data. Constructing such references requires integration of …