Current best practices in single‐cell RNA‐seq analysis: a tutorial

Molecular Systems Biology, Год журнала: 2019, Номер 15(6)

Опубликована: Июнь 1, 2019

Single-cell RNA-seq has enabled gene expression to be studied at an unprecedented resolution. The promise of this technology is attracting a growing user base for single-cell analysis methods. As more tools are becoming available, it increasingly difficult navigate landscape and produce up-to-date workflow analyse one's data. Here, we detail the steps typical analysis, including pre-processing (quality control, normalization, data correction, feature selection, dimensionality reduction) cell- gene-level downstream analysis. We formulate current best-practice recommendations these based on independent comparison studies. have integrated into workflow, which apply public dataset further illustrate how work in practice. Our documented case study can found https://www.github.com/theislab/single-cell-tutorial This review will serve as tutorial new entrants field, help established users update their pipelines.

Язык: Английский

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Cells of the adult human heart

Nature, Год журнала: 2020, Номер 588(7838), С. 466 - 472

Опубликована: Сен. 24, 2020

Abstract Cardiovascular disease is the leading cause of death worldwide. Advanced insights into mechanisms and therapeutic strategies require a deeper understanding molecular processes involved in healthy heart. Knowledge full repertoire cardiac cells their gene expression profiles fundamental first step this endeavour. Here, using state-of-the-art analyses large-scale single-cell single-nucleus transcriptomes, we characterize six anatomical adult heart regions. Our results highlight cellular heterogeneity cardiomyocytes, pericytes fibroblasts, reveal distinct atrial ventricular subsets with diverse developmental origins specialized properties. We define complexity vasculature its changes along arterio-venous axis. In immune compartment, identify cardiac-resident macrophages inflammatory protective transcriptional signatures. Furthermore, cell-to-cell interactions different networks macrophages, fibroblasts cardiomyocytes between atria ventricles that are from those skeletal muscle. human cell atlas improves our provides valuable reference for future studies.

Язык: Английский

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A single–cell type transcriptomics map of human tissues

Science Advances, Год журнала: 2021, Номер 7(31)

Опубликована: Июль 28, 2021

Single-cell RNA analysis has been integrated with spatial protein profiling to create a single–cell type map of human tissues.

Язык: Английский

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Microglia states and nomenclature: A field at its crossroads

Neuron, Год журнала: 2022, Номер 110(21), С. 3458 - 3483

Опубликована: Ноя. 1, 2022

Язык: Английский

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SARS‐CoV‐2 receptorACE2 andTMPRSS2 are primarily expressed in bronchial transient secretory cells

The EMBO Journal, Год журнала: 2020, Номер 39(10)

Опубликована: Апрель 14, 2020

The SARS-CoV-2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID-19 pathogenesis, especially host factors facilitating virus infection replication. was reported to enter cells via binding ACE2, followed by its priming TMPRSS2. Here, we investigate ACE2 TMPRSS2 expression levels their distribution across cell types in lung tissue (twelve donors, 39,778 cells) derived from subsegmental bronchial branches (four 17,521 single nuclei RNA sequencing, respectively. While is strongly expressed both tissues, predominantly a transient secretory type. Interestingly, these transiently differentiating show an enrichment pathways related RHO GTPase function viral processes suggesting increased vulnerability infection. Our data provide rich resource future investigations pathogenesis.

Язык: Английский

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A scalable SCENIC workflow for single-cell gene regulatory network analysis

Nature Protocols, Год журнала: 2020, Номер 15(7), С. 2247 - 2276

Опубликована: Июнь 19, 2020

Язык: Английский

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Deciphering cell–cell interactions and communication from gene expression

Nature Reviews Genetics, Год журнала: 2020, Номер 22(2), С. 71 - 88

Опубликована: Ноя. 9, 2020

Язык: Английский

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Benchmarking atlas-level data integration in single-cell genomics

Nature Methods, Год журнала: 2021, Номер 19(1), С. 41 - 50

Опубликована: Дек. 23, 2021

Abstract 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 reliable data integration. To guide integration method choice, we benchmarked 68 preprocessing combinations on 85 batches gene expression, chromatin accessibility simulation from 23 publications, altogether representing >1.2 million cells distributed 13 atlas-level tasks. We evaluated methods according scalability, usability their ability remove while retaining biological variation using 14 evaluation metrics. show highly variable selection improves the performance methods, whereas scaling pushes prioritize removal over conservation variation. Overall, scANVI, Scanorama, scVI scGen perform well, particularly complex tasks, single-cell ATAC-sequencing is strongly affected by choice feature space. Our freely available Python module benchmarking pipeline can identify optimal for new data, benchmark improve development.

Язык: Английский

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Single‐cell RNA sequencing technologies and applications: A brief overview

Clinical and Translational Medicine, Год журнала: 2022, Номер 12(3)

Опубликована: Март 1, 2022

Язык: Английский

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Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics

Nature Reviews Genetics, Год журнала: 2021, Номер 22(10), С. 627 - 644

Опубликована: Июнь 18, 2021

Язык: Английский

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