Eleven grand challenges in single-cell data science
The recent boom in microfluidics and combinatorial indexing strategies, combined with low
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
sequencing costs, has empowered single-cell sequencing technology. Thousands—or even …
Lineage tracing meets single-cell omics: opportunities and challenges
A fundamental goal of developmental and stem cell biology is to map the developmental
history (ontogeny) of differentiated cell types. Recent advances in high-throughput single …
history (ontogeny) of differentiated cell types. Recent advances in high-throughput single …
Nasal ciliated cells are primary targets for SARS-CoV-2 replication in the early stage of COVID-19
The upper respiratory tract is compromised in the early period of COVID-19, but SARS-CoV-
2 tropism at the cellular level is not fully defined. Unlike recent single-cell RNA-Seq analyses …
2 tropism at the cellular level is not fully defined. Unlike recent single-cell RNA-Seq analyses …
Single-cell DNA methylation and 3D genome architecture in the human brain
Delineating the gene-regulatory programs underlying complex cell types is fundamental for
understanding brain function in health and disease. Here, we comprehensively examined …
understanding brain function in health and disease. Here, we comprehensively examined …
Single-cell transcriptional diversity is a hallmark of developmental potential
Single-cell RNA sequencing (scRNA-seq) is a powerful approach for reconstructing cellular
differentiation trajectories. However, inferring both the state and direction of differentiation is …
differentiation trajectories. However, inferring both the state and direction of differentiation is …
Trajectory-based differential expression analysis for single-cell sequencing data
Trajectory inference has radically enhanced single-cell RNA-seq research by enabling the
study of dynamic changes in gene expression. Downstream of trajectory inference, it is vital …
study of dynamic changes in gene expression. Downstream of trajectory inference, it is vital …
Temporal modelling using single-cell transcriptomics
Methods for profiling genes at the single-cell level have revolutionized our ability to study
several biological processes and systems including development, differentiation, response …
several biological processes and systems including development, differentiation, response …
Embracing the dropouts in single-cell RNA-seq analysis
One primary reason that makes single-cell RNA-seq analysis challenging is dropouts, where
the data only captures a small fraction of the transcriptome of each cell. Almost all …
the data only captures a small fraction of the transcriptome of each cell. Almost all …
Assessment of computational methods for the analysis of single-cell ATAC-seq data
Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin
using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands …
using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands …
Pathway-based classification of glioblastoma uncovers a mitochondrial subtype with therapeutic vulnerabilities
The transcriptomic classification of glioblastoma (GBM) has failed to predict survival and
therapeutic vulnerabilities. A computational approach for unbiased identification of core …
therapeutic vulnerabilities. A computational approach for unbiased identification of core …