An interpretable single-cell RNA sequencing data clustering method based on latent Dirichlet allocation DOI Creative Commons
Qi Yang, Zhaochun Xu, Wenyang Zhou

et al.

Briefings in Bioinformatics, Journal Year: 2023, Volume and Issue: 24(4)

Published: May 23, 2023

Single-cell RNA sequencing (scRNA-seq) detects whole transcriptome signals for large amounts of individual cells and is powerful determining cell-to-cell differences investigating the functional characteristics various cell types. scRNA-seq datasets are usually sparse highly noisy. Many steps in analysis workflow, including reasonable gene selection, clustering annotation, as well discovering underlying biological mechanisms from such datasets, difficult. In this study, we proposed an method based on latent Dirichlet allocation (LDA) model. The LDA model estimates a series variables, i.e. putative functions (PFs), input raw cell-gene data. Thus, incorporated 'cell-function-gene' three-layer framework into analysis, capable complex expression patterns via built-in approach obtaining biologically meaningful results through data-driven interpretation process. We compared our with four classic methods seven benchmark datasets. LDA-based performed best test terms both accuracy purity. By analysing three public demonstrated that could distinguish types multiple levels specialization, precisely reconstruct development trajectories. Moreover, accurately identified representative PFs genes types/cell stages, enabling cluster annotation interpretation. According to literature, most previously reported marker/functionally relevant were recognized.

Language: Английский

scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data DOI Open Access
Fan Yang, Wenchuan Wang, Fang Wang

et al.

Nature Machine Intelligence, Journal Year: 2022, Volume and Issue: 4(10), P. 852 - 866

Published: Sept. 26, 2022

Language: Английский

Citations

275
Applications of single-cell RNA sequencing in drug discovery and development DOI Creative Commons
Bram Van de Sande, Joon Sang Lee, Euphemia Mutasa-Gottgens

et al.

Nature Reviews Drug Discovery, Journal Year: 2023, Volume and Issue: 22(6), P. 496 - 520

Published: April 28, 2023

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery development. New opportunities emerging in target identification owing to improved disease understanding through cell subtyping, highly multiplexed functional genomics screens incorporating scRNA-seq enhancing credentialling prioritization. ScRNA-seq is also aiding selection relevant preclinical models providing new insights into mechanisms action. In clinical development, can inform decision-making via biomarker for patient stratification more precise monitoring response progression. Here, we illustrate how methods being applied key steps discuss ongoing challenges their implementation pharmaceutical industry. There have been significant recent advances development remarkable Ferran colleagues primarily pipeline, from decision-making. Ongoing potential future directions discussed.

Language: Английский

Citations

207
Using clusterProfiler to characterize multiomics data DOI
Shuangbin Xu, Erqiang Hu, Yantong Cai

et al.

Nature Protocols, Journal Year: 2024, Volume and Issue: 19(11), P. 3292 - 3320

Published: July 17, 2024

Language: Английский

Citations

158
A transcription factor atlas of directed differentiation DOI Creative Commons
Julia Joung, Sai Ma, Tristan Tay

et al.

Cell, Journal Year: 2023, Volume and Issue: 186(1), P. 209 - 229.e26

Published: Jan. 1, 2023

Transcription factors (TFs) regulate gene programs, thereby controlling diverse cellular processes and cell states. To comprehensively understand TFs the programs they control, we created a barcoded library of all annotated human TF splice isoforms (>3,500) applied it to build Atlas charting expression profiles embryonic stem cells (hESCs) overexpressing each at single-cell resolution. We mapped TF-induced reference types validated candidate for generation types, spanning three germ layers trophoblasts. Targeted screens with subsets allowed us create tailored disease model integrate mRNA chromatin accessibility data identify downstream regulators. Finally, characterized effects combinatorial overexpression by developing validating strategy predicting combinations that produce target matching accelerate engineering efforts.

Language: Английский

Citations

119
Harmonized single-cell landscape, intercellular crosstalk and tumor architecture of glioblastoma DOI Creative Commons
Cristian Ruiz-Moreno, Sergio Marco Salas, Erik Samuelsson

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2022, Volume and Issue: unknown

Published: Aug. 27, 2022

SUMMARY Glioblastoma, isocitrate dehydrogenase (IDH)-wildtype (hereafter, GB), is an aggressive brain malignancy associated with a dismal prognosis and poor quality of life. Single-cell RNA sequencing has helped to grasp the complexity cell states dynamic changes in GB. Large-scale data integration can help uncover unexplored tumor pathobiology. Here, we resolved composition milieu created cellular map GB (‘GBmap’), curated resource that harmonizes 26 datasets gathering 240 patients spanning over 1.1 million cells. We showcase applications our for reference mapping, transfer learning, biological discoveries. Our results sources pro-angiogenic signaling multifaceted role mesenchymal-like cancer Reconstructing architecture using spatially transcriptomics unveiled high level well-structured neoplastic niches. The GBmap represents framework allows streamlined interpretation new provides platform exploratory analysis, hypothesis generation testing.

Language: Английский

Citations

85
Delineating the dynamic evolution from preneoplasia to invasive lung adenocarcinoma by integrating single-cell RNA sequencing and spatial transcriptomics DOI Creative Commons
Jianfei Zhu, Yue Fan, Yanlu Xiong

et al.

Experimental & Molecular Medicine, Journal Year: 2022, Volume and Issue: 54(11), P. 2060 - 2076

Published: Nov. 25, 2022

Abstract The cell ecology and spatial niche implicated in the dynamic sequential process of lung adenocarcinoma (LUAD) from situ (AIS) to minimally invasive (MIA) subsequent (IAC) have not yet been elucidated. Here, we performed an integrative analysis single-cell RNA sequencing (scRNA-seq) transcriptomics (ST) characterize atlas invasion trajectory LUAD. We found that UBE2C + cancer subpopulation constantly increased during LUAD with remarkable elevation IAC, its distribution was peripheral region representing a more malignant phenotype. Furthermore, TME type showed constant decrease mast cells, monocytes, lymphatic endothelial which were whole LUAD, accompanied by increase NK cells MALT B AIS MIA Tregs secretory IAC. Notably, for AIS, colocalized region; however, cells. Finally, communication interaction between cell-induced constitutive activation TGF-β signaling involved Therefore, our results reveal specific cellular information architecture subpopulations, as well them, will facilitate identification development precision medicine

Language: Английский

Citations

82
ALKBH5/MAP3K8 axis regulates PD-L1+ macrophage infiltration and promotes hepatocellular carcinoma progression DOI Creative Commons
Yu You, Diguang Wen,

Lu Zeng

et al.

International Journal of Biological Sciences, Journal Year: 2022, Volume and Issue: 18(13), P. 5001 - 5018

Published: Jan. 1, 2022

Hepatocellular carcinoma is one of the most common malignant tumors.M6A a novel epigenetic modification that have been emerged as vital regulators for progression HCC.However, regulatory role, clinical significance and details modification, such impact on local tumor environment, remain largely unclear.Our study showed ALKBH5 was highly expressed in HCC high expression predicted worse prognosis patients.Prediction function by tissue samples single cell sequencing Gene Set Variation Analysis.Primary CD3 + T lymphocytes bone marrow-derived macrophages were used to evaluate effect immune microenvironment.The results indicated promote proliferation, metastasis PD-L1+macrophage recruitment.Mechanistically regulates MAP3K8 m6A dependent manner which mediates proliferation cells.ALKBH5 also promotes activation JNK ERK pathways through upregulating MAP3K8, thus regulating IL-8 promoting macrophage recruitment.Taken together, these data show growth, recruitment ALKBH5/MAP3K8 axis it may serve potential diagnostic marker target treatment patients.

Language: Английский

Citations

75
Comparative analysis of cell–cell communication at single-cell resolution DOI Open Access
Aaron J. Wilk, Alex K. Shalek, Susan Holmes

et al.

Nature Biotechnology, Journal Year: 2023, Volume and Issue: 42(3), P. 470 - 483

Published: May 11, 2023

Language: Английский

Citations

62
The neuroimmune response during stress: A physiological perspective DOI Creative Commons
Hedva Haykin, Asya Rolls

Immunity, Journal Year: 2021, Volume and Issue: 54(9), P. 1933 - 1947

Published: Sept. 1, 2021

Language: Английский

Citations

63
Integrating single-cell sequencing data with GWAS summary statistics reveals CD16+monocytes and memory CD8+T cells involved in severe COVID-19 DOI Creative Commons
Yunlong Ma, Fei Qiu, Chunyu Deng

et al.

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

Published: Feb. 17, 2022

Understanding the host genetic architecture and viral immunity contributes to development of effective vaccines therapeutics for controlling COVID-19 pandemic. Alterations immune responses in peripheral blood mononuclear cells play a crucial role detrimental progression COVID-19. However, effects factors on severe remain largely unknown.We constructed computational framework characterize genetics that influence cell subpopulations by integrating GWAS summary statistics (N = 969,689 samples) with four independent scRNA-seq datasets containing healthy controls patients mild, moderate, symptom 606,534 cells). We collected 10 predefined gene sets including inflammatory cytokine genes calculate state score evaluating immunological features individual cells.We found 34 risk were significantly associated COVID-19, number highly expressed increased severity Three subtypes are CD16+monocytes, megakaryocytes, memory CD8+T enriched COVID-19-related association signals. Notably, three causal CCR1, CXCR6, ABO these types, respectively. CCR1+CD16+monocytes ABO+ megakaryocytes up-regulated genes, S100A12, S100A8, S100A9, IFITM1, confer higher dysregulated response among patients. CXCR6+ CD8+ T exhibit notable polyfunctionality elevation proliferation, migration, chemotaxis. Moreover, we observed an increase cell-cell interactions both CCR1+ CD16+monocytes compared normal PBMCs lung tissues. The enhanced epithelial facilitate recruitment this specific population airways, promoting cell-mediated against infection.We uncover major genetics-modulated shift between mild infection, elevated expression genetics-risk cytokines, functional subsets aggravating disease severity, which provides novel insights into parsing determinants

Language: Английский

Citations

55