hypeR: An R Package for Geneset Enrichment Workflows

Federico, Anthony; Monti, Stefano

doi:10.1101/656637

Cited by 35 publications

(44 citation statements)

References 7 publications

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“…Pathways with log-fold-change > 0.05 and an adjusted P < 0.01 were considered as significantly upregulated. GO and REACOTOME geneset enrichment analyses were performed using hypeR package, 100 geneset over-representation was determined by hypergeometric test.…”

Section: Methodsmentioning

confidence: 99%

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

et al. 2020

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The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer ( n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4 + T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

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Section: Methodsmentioning

confidence: 99%

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

et al. 2020

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“…Subsequently, glia cells were further processed and categorized into major glia types (e.g. Radial glia (NSC), Astrocyte Precursor Cells (APC)-Astrocytes, Oligoprogenitors (OPCs), and Oligodendrocytes) employing customized glia cell specific marker genes enrichment analysis implemented in hypeR ( Federico and Monti, 2019 ). Glia cell type specific gene expression of the five candidate receptors were visualized by R package Pheatmap v1.012.…”

Section: Methodsmentioning

confidence: 99%

Novel C1q receptor-mediated signaling controls neural stem cell behavior and neurorepair

Benavente

Piltti²,

Hooshmand³

et al. 2020

eLife

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C1q plays a key role as a recognition molecule in the immune system, driving autocatalytic complement cascade activation and acting as an opsonin. We have previously reported a non-immune role of complement C1q modulating the migration and fate of human neural stem cells (hNSC); however, the mechanism underlying these effects has not yet been identified. Here, we show for the first time that C1q acts as a functional hNSC ligand, inducing intracellular signaling to control cell behavior. Using an unbiased screening strategy, we identified five transmembrane C1q signaling/receptor candidates in hNSC (CD44, GPR62, BAI1, c-MET, and ADCY5). We further investigated the interaction between C1q and CD44 , demonstrating that CD44 mediates C1q induced hNSC signaling and chemotaxis in vitro, and hNSC migration and functional repair in vivo after spinal cord injury. These results reveal a receptor-mediated mechanism for C1q modulation of NSC behavior and show that modification of C1q receptor expression can expand the therapeutic window for hNSC transplantation.

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“…Pathways with median fold change >3 and an adjusted p-value < 0.01 were considered as significantly changed. GO and REACTOME geneset enrichment analysis were performed using hypeR package 61 ; geneset over-representation was determined by hypergeometric test.…”

Section: Inflammatory Pathways and Gene Set Enrichment Analysis And Tmentioning

confidence: 99%

Discriminating Mild from Critical COVID-19 by Innate and Adaptive Immune Single-cell Profiling of Bronchoalveolar Lavages

Wauters

Mol

Garg

et al. 2020

Preprint

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How innate and adaptive lung immune responses to SARS-CoV-2 synchronize during COVID-19 pneumonitis and regulate disease severity is poorly established. To address this, we applied single-cell profiling to bronchoalveolar lavages from 44 patients with mild or critical COVID-19 versus non-COVID-19 pneumonia as control. Viral RNA-tracking delineated the infection phenotype to epithelial cells, but positioned mainly neutrophils at the forefront of viral clearance activity during COVID-19. In mild disease, neutrophils could execute their antiviral function in an immunologically controlled fashion, regulated by fully-differentiated T-helper-17 (TH17)-cells, as well as T-helper-1 (TH1)-cells, CD8+ resident-memory (TRM) and partially-exhausted (TEX) T-cells with good effector functions. This was paralleled by orderly phagocytic disposal of dead/stressed cells by fully-differentiated macrophages, otherwise characterized by anti-inflammatory and antigen-presenting characteristics, hence facilitating lung tissue repair. In critical disease, CD4+ TH1- and CD8+ TEX-cells were characterized by inflammation-associated stress and metabolic exhaustion, while CD4+ TH17- and CD8+ TRM-cells failed to differentiate. Consequently, T-cell effector function was largely impaired thereby possibly facilitating excessive neutrophil-based inflammation. This was accompanied by impaired monocyte-to-macrophage differentiation, with monocytes exhibiting an ATP-purinergic signalling-inflammasome footprint, thereby enabling COVID-19 associated fibrosis and worsening disease severity. Our work represents a major resource for understanding the lung-localised immunity and inflammation landscape during COVID-19.

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hypeR: An R Package for Geneset Enrichment Workflows

Cited by 35 publications

References 7 publications

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

A pan-cancer blueprint of the heterogeneous tumor microenvironment revealed by single-cell profiling

Novel C1q receptor-mediated signaling controls neural stem cell behavior and neurorepair

Discriminating Mild from Critical COVID-19 by Innate and Adaptive Immune Single-cell Profiling of Bronchoalveolar Lavages

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