The joint analysis of the genome, epigenome, transcriptome, proteome and/or metabolome
from single cells is transforming our understanding of cell biology in health and disease. In …

Single‐cell RNA sequencing (scRNA‐seq) technology has become the state‐of‐the‐art
approach for unravelling the heterogeneity and complexity of RNA transcripts within …

Soil microorganisms are clearly a key component of both natural and managed ecosystems.
Despite the challenges of surviving in soil, a gram of soil can contain thousands of individual …

The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …

Deep learning describes a class of machine learning algorithms that are capable of
combining raw inputs into layers of intermediate features. These algorithms have recently …

Although single-cell RNA sequencing studies have begun to provide compendia of cell
expression profiles,,,,,,,–, it has been difficult to systematically identify and localize all …

Challenges in cultivating microorganisms have limited the phylogenetic diversity of currently
available microbial genomes. This is being addressed by advances in sequencing …

In recent years, exceptional technological advances have enabled the identification and
interrogation of rare circulating tumour cells (CTCs) from blood samples of patients, leading …

Advances in single-cell isolation and barcoding technologies offer unprecedented
opportunities to profile DNA, mRNA, and proteins at a single-cell resolution. Recently, bulk …

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel
profiling of transcriptomes. However, assessing differential expression across multiple …