Best practices for single-cell analysis across modalities
Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
Gene regulatory network inference in the era of single-cell multi-omics
P Badia-i-Mompel, L Wessels, S Müller-Dott… - Nature Reviews …, 2023 - nature.com
The interplay between chromatin, transcription factors and genes generates complex
regulatory circuits that can be represented as gene regulatory networks (GRNs). The study …
regulatory circuits that can be represented as gene regulatory networks (GRNs). The study …
Dissection of artifactual and confounding glial signatures by single-cell sequencing of mouse and human brain
A key aspect of nearly all single-cell sequencing experiments is dissociation of intact tissues
into single-cell suspensions. While many protocols have been optimized for optimal cell …
into single-cell suspensions. While many protocols have been optimized for optimal cell …
Applications of single-cell RNA sequencing in drug discovery and development
B Van de Sande, JS Lee, E Mutasa-Gottgens… - Nature Reviews Drug …, 2023 - nature.com
Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods,
together with associated computational tools and the growing availability of public data …
together with associated computational tools and the growing availability of public data …
A new gene set identifies senescent cells and predicts senescence-associated pathways across tissues
Although cellular senescence drives multiple age-related co-morbidities through the
senescence-associated secretory phenotype, in vivo senescent cell identification remains …
senescence-associated secretory phenotype, in vivo senescent cell identification remains …
Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues
Spatial transcriptomics (ST) technologies generate multiple data types from biological
samples, namely gene expression, physical distance between data points, and/or tissue …
samples, namely gene expression, physical distance between data points, and/or tissue …
A guide for the diagnosis of rare and undiagnosed disease: beyond the exome
Rare diseases affect 30 million people in the USA and more than 300–400 million
worldwide, often causing chronic illness, disability, and premature death. Traditional …
worldwide, often causing chronic illness, disability, and premature death. Traditional …
Deciphering cell–cell interactions and communication from gene expression
E Armingol, A Officer, O Harismendy… - Nature Reviews …, 2021 - nature.com
Cell–cell interactions orchestrate organismal development, homeostasis and single-cell
functions. When cells do not properly interact or improperly decode molecular messages …
functions. When cells do not properly interact or improperly decode molecular messages …
Computational principles and challenges in single-cell data integration
The development of single-cell multimodal assays provides a powerful tool for investigating
multiple dimensions of cellular heterogeneity, enabling new insights into development …
multiple dimensions of cellular heterogeneity, enabling new insights into development …
Interpretation of T cell states from single-cell transcriptomics data using reference atlases
Single-cell RNA sequencing (scRNA-seq) has revealed an unprecedented degree of
immune cell diversity. However, consistent definition of cell subtypes and cell states across …
immune cell diversity. However, consistent definition of cell subtypes and cell states across …