Cell2location maps fine-grained cell types in spatial transcriptomics

Kleshchevnikov, Vitalii; Shmatko, Artem; Dann, Emma; Aivazidis, Alexander; King, Hamish W; Li, Tong; Elmentaite, Rasa; Lomakin, Artem; Kedlian, Veronika R.; Gayoso, Adam; Jain, Mika Sarkin; Park, Jun Sung; Ramona, Lauma; Tuck, Elizabeth; Arutyunyan, Anna; Vento‐Tormo, Roser; Gerstung, Moritz; James, Louisa K.; Stegle, Oliver; Bayraktar, Omer Ali

doi:10.1038/s41587-021-01139-4

Cited by 592 publications

(704 citation statements)

References 60 publications

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“…Next, we compared the performance of STRIDE with other published cell-type deconvolution tools, including methods developed for spatial transcriptomics, such as SPOTlight(19), NMFreg(9), Seurat CCA(36), RCTD(21), and cell2location(22), as well as the ones for bulk RNA-seq, such as CIBERSORTx(37) and EPIC(38). STRIDE showed the highest concordance between the prediction and the ground truth, and RCTD and cell2location showed slightly worse consistency (Figure 2D).…”

Section: Resultsmentioning

confidence: 99%

“…Previous studies performed enrichment analysis using the gene signature derived from scRNA-seq (16,18), the utility of which is limited by the incomparability of the scores across different spatial locations or slides. On the contrary, the deconvolution methods aim to estimate the exact cell type proportions for each spatial location, either by applying regression models (9,19,20) or through fitting probability distributions (21,22). However, most of the existing deconvolution methods depend on the marker genes inferred from single-cell reference, which might suffer from the high drop-out rate and unwanted gene expression fluctuations.…”

Section: Introductionmentioning

confidence: 99%

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STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Sun

Xiao

Liu

et al. 2021

Preprint

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The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity in the spatial context. However, the current limitations of spatial technologies hamper the exploration of cellular localizations and interactions at single-cell level. Here, we present spatial transcriptomics deconvolution by topic modeling (STRIDE), a computational method to decompose cell-types from spatial mixtures by leveraging topic profiles trained from single-cell transcriptomics. STRIDE accurately estimated the cell-type proportions and showed balanced specificity and sensitivity compared to existing methods. We demonstrate STRIDE's utility by applying it to different spatial platforms and biological systems. Deconvolution by STRIDE not only mapped rare cell-types to spatial locations but also improved the identification of spatial localized genes and domains. Moreover, topics discovered by STRIDE were associated with cell-type-specific functions, and could be further used to integrate successive sections and reconstruct the three-dimensional architecture of tissues. Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics and is publicly available at https://github.com/DongqingSun96/STRIDE.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Sun

Xiao

Liu

et al. 2021

Preprint

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“…To further confirm neuronal subtype identity, we compared our dataset with publicly available spatial transcriptomic data from cell2location 57 . While mRNA signatures from broad cluster categories such as astrocytes (Supplementary Figure 5) do not show restriction to one or more hypothalamic subnuclei, the mRNA signatures of specific neuronal subclusters are localized in discrete locations.…”

Section: Resultsmentioning

confidence: 99%

Single cell analysis of the aging female hypothalamus

Hajdarovic

Hassell

et al. 2021

Preprint

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Alterations in metabolism, sleep patterns, body composition, and hormone status are all key features of aging. The hypothalamus is a well-conserved brain region that controls these homeostatic and survival-related behaviors. Despite the importance of this brain region in healthy aging, little is known about the intrinsic features of hypothalamic aging. Here, we utilize single nuclei RNA-sequencing to assess the transcriptomes of 22,718 hypothalamic nuclei from young and aged female mice. We identify cell type-specific signatures of aging in neurons, astrocytes, and microglia, as well as among the diverse collection of neuronal subtypes in this region. We uncover key changes in cell types critical for metabolic regulation and body composition, as well as in an area of the hypothalamus linked to cognition. In addition, our analysis reveals female-specific changes in sex chromosome regulation in the aging brain. This study identifies critical cell-specific features of the aging hypothalamus in mammals.

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“…(C) Violin plots and spatial mapping of counts and features across Visium spots. (D) Schematic of spatial mapping approach using cell2location (60) and examples of cell cluster mapping.…”

Section: Supplementary Data Figuresmentioning

confidence: 99%

Single-cell analyses of axolotl forebrain organization, neurogenesis, and regeneration

Lust

Maynard

Gomes

et al. 2022

Preprint

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Salamanders are important tetrapod models to study brain organization and regeneration, however the identity and evolutionary conservation of brain cell types is largely unknown. Here, we delineate cell populations in the axolotl telencephalon during homeostasis and regeneration, representing the first single-cell genomic and spatial profiling of an anamniote tetrapod brain. We identify glutamatergic neurons with similarities to amniote neurons of hippocampus, dorsal and lateral cortex, and conserved GABAergic neuron classes. We infer transcriptional dynamics and gene regulatory relationships of postembryonic, region-specific direct and indirect neurogenesis, and unravel conserved signatures. Following brain injury, ependymoglia activate an injury-specific state before reestablishing lost neuron populations and axonal connections. Together, our analyses yield key insights into the organization, evolution, and regeneration of a tetrapod nervous system.

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Cell2location maps fine-grained cell types in spatial transcriptomics

Cited by 592 publications

References 60 publications

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

STRIDE: accurately decomposing and integrating spatial transcriptomics using single-cell RNA sequencing

Single cell analysis of the aging female hypothalamus

Single-cell analyses of axolotl forebrain organization, neurogenesis, and regeneration

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