Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients

Cell, Journal Year: 2020, Volume and Issue: 181(7), P. 1475 - 1488.e12

Published: May 8, 2020

Language: Английский

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An introduction to spatial transcriptomics for biomedical research

Genome Medicine, Journal Year: 2022, Volume and Issue: 14(1)

Published: June 27, 2022

Abstract Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over the past decade, particularly in developmental biology, cancer, immunology, and neuroscience. Most commercially available scRNA-seq protocols require cells to be recovered intact viable from tissue. This precluded many cell types study largely destroys spatial context that could otherwise inform analyses of identity function. An increasing number platforms now facilitate spatially resolved, high-dimensional assessment gene transcription, known as ‘spatial transcriptomics’. Here, we introduce different classes method, which either record locations hybridized mRNA molecules tissue, image positions themselves prior assessment, or employ arrays probes pre-determined location. We review sizes tissue area can assessed, their resolution, genes profiled. discuss if preservation influences choice platform, provide guidance on whether specific may better suited discovery screens hypothesis testing. Finally, bioinformatic methods analysing transcriptomic data, including pre-processing, integration with existing inference cell-cell interactions. Spatial -omics are already improving our understanding human tissues research, diagnostic, therapeutic settings. To build upon these recent advancements, entry-level those seeking own research.

Language: Английский

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Ageing hallmarks exhibit organ-specific temporal signatures

Nature, Journal Year: 2020, Volume and Issue: 583(7817), P. 596 - 602

Published: July 15, 2020

Language: Английский

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Feature selection and dimension reduction for single-cell RNA-Seq based on a multinomial model

Genome biology, Journal Year: 2019, Volume and Issue: 20(1)

Published: Dec. 1, 2019

Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs). Using negative controls, we show UMI counts follow multinomial sampling with no zero inflation. Current normalization procedures such as log per million and feature selection by highly variable genes produce false variability in dimension reduction. We propose simple methods, including generalized principal component analysis (GLM-PCA) for non-normal distributions, using deviance. These methods outperform the current practice a downstream clustering assessment ground truth datasets.

Language: Английский

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Spatiotemporal Immune Landscape of Colorectal Cancer Liver Metastasis at Single-Cell Level

Cancer Discovery, Journal Year: 2021, Volume and Issue: 12(1), P. 134 - 153

Published: Aug. 20, 2021

Abstract Liver metastasis, the leading cause of colorectal cancer mortality, exhibits a highly heterogeneous and suppressive immune microenvironment. Here, we sequenced 97 matched samples by using single-cell RNA sequencing spatial transcriptomics. Strikingly, metastatic microenvironment underwent remarkable reprogramming immunosuppressive cells such as MRC1+ CCL18+ M2-like macrophages. We further developed scMetabolism, computational pipeline for quantifying metabolism, observed that those macrophages harbored enhanced metabolic activity. Interestingly, neoadjuvant chemotherapy could block this status restore antitumor balance in responsive patients, whereas nonresponsive patients deteriorated into more one. Our work described evolution metastasis uncovered black box how tumors respond to chemotherapy. Significance: present atlas liver found metabolically activated sites. Efficient can slow down activation, raising possibility target metabolism pathways metastasis. This article is highlighted In Issue feature, p. 1

Language: Английский

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