Annotation of spatially resolved single-cell data with STELLAR DOI
Maria Brbić, Kaidi Cao, John W. Hickey

et al.

Nature Methods, Journal Year: 2022, Volume and Issue: 19(11), P. 1411 - 1418

Published: Oct. 24, 2022

Language: Английский

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

83

An integrated single cell and spatial transcriptomic map of human white adipose tissue DOI Creative Commons
Lucas Massier, Jutta Jalkanen, Merve Elmastas

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: March 15, 2023

Abstract To date, single-cell studies of human white adipose tissue (WAT) have been based on small cohort sizes and no cellular consensus nomenclature exists. Herein, we performed a comprehensive meta-analysis publicly available newly generated single-cell, single-nucleus, spatial transcriptomic results from subcutaneous, omental, perivascular WAT. Our high-resolution map is built data ten allowed us to robustly identify >60 subpopulations adipocytes, fibroblast adipogenic progenitors, vascular, immune cells. Using these results, deconvolved bulk nine additional cohorts provide clinical dimensions the map. This identified cell-cell interactions as well relationships between specific cell subtypes insulin resistance, dyslipidemia, adipocyte volume, lipolysis upon long-term weight changes. Altogether, our meta-map provides rich resource defining microarchitectural landscape WAT describes associations types metabolic states.

Language: Английский

Citations

83

Integrated single-nucleus and spatial transcriptomics captures transitional states in soybean nodule maturation DOI
Zhijian Liu,

Xiangying Kong,

Yanping Long

et al.

Nature Plants, Journal Year: 2023, Volume and Issue: 9(4), P. 515 - 524

Published: April 13, 2023

Language: Английский

Citations

81

An integrated cell atlas of the human lung in health and disease DOI Creative Commons
Lisa Sikkema, Daniel Strobl, Luke Zappia

et al.

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

Published: March 11, 2022

ABSTRACT Organ- and body-scale cell atlases have the potential to transform our understanding of human biology. To capture variability present in population, these must include diverse demographics such as age ethnicity from both healthy diseased individuals. The growth size number single-cell datasets, combined with recent advances computational techniques, for first time makes it possible generate comprehensive large-scale through integration multiple datasets. Here, we integrated Human Lung Cell Atlas (HLCA) combining 46 datasets respiratory system into a single atlas spanning over 2.2 million cells 444 individuals across health disease. HLCA contains consensus re-annotation published newly generated resolving under- or misannotation 59% original enables recovery rare types, provides marker genes each type, uncovers gene modules associated demographic covariates anatomical location within system. facilitate use reference lung research allow rapid analysis new data, provide an interactive web portal project onto HLCA. Finally, demonstrate value interpreting disease-associated changes. Thus, outlines roadmap development organ-scale Atlas.

Language: Английский

Citations

80

Annotation of spatially resolved single-cell data with STELLAR DOI
Maria Brbić, Kaidi Cao, John W. Hickey

et al.

Nature Methods, Journal Year: 2022, Volume and Issue: 19(11), P. 1411 - 1418

Published: Oct. 24, 2022

Language: Английский

Citations

72