Spatially resolved sampling for untargeted metabolomics: A new tool for salivomics

Ciurli, Alessio; Liebl, Maximiliam; Derks, Rico; Neefjes, Jacques; Giera, Martin

doi:10.1016/j.isci.2021.102768

Cited by 6 publications

(11 citation statements)

References 27 publications

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“…Furthermore, Maguire et al (2020) used ggVennDiagram to confirm that their novel method has low bias and is more sensitive than three other methods for small RNA library preparation. In addition, ggVennDiagram is also used for analyzing the differences between several spatially varied oral metabolomics samples ( Ciurli et al, 2021 ) and for comparing single-nucleotide variants between tumor and non-tumor tissues ( Horny et al, 2021 ). So far, ggVennDiagram has been cited in more than 20 peer-reviewed articles and open-access preprints, as retrieved by Google Scholar.…”

Section: Resultsmentioning

confidence: 99%

“…Furthermore, Maguire et al (2020) used ggVennDiagram to confirm that their novel method has low bias and is more sensitive than three other methods for small RNA library preparation. In addition, ggVennDiagram is also used for analyzing the differences between several spatially varied oral metabolomics samples (Ciurli et al, 2021) and for comparing FIGURE 4 | Plots generated by the tools listed in Table 1. The used tools are ggVennDiagram, VennDiagram, colorfulVennPlot, venn, nVennR, eulerr, RVenn, gplots, interactiVenn, and Venny (A-K), respectively.…”

Section: Integration Of Ggvenndiagram Into Bioinformatics Analysis Pipelinesmentioning

confidence: 99%

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ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

2021

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Venn diagrams are widely used diagrams to show the set relationships in biomedical studies. In this study, we developed ggVennDiagram, an R package that could automatically generate high-quality Venn diagrams with two to seven sets. The ggVennDiagram is built based on ggplot2, and it integrates the advantages of existing packages, such as venn, RVenn, VennDiagram, and sf. Satisfactory results can be obtained with minimal configurations. Furthermore, we designed comprehensive objects to store the entire data of the Venn diagram, which allowed free access to both intersection values and Venn plot sub-elements, such as set label/edge and region label/filling. Therefore, high customization of every Venn plot sub-element can be fulfilled without increasing the cost of learning when the user is familiar with ggplot2 methods. To date, ggVennDiagram has been cited in more than 10 publications, and its source code repository has been starred by more than 140 GitHub users, suggesting a great potential in applications. The package is an open-source software released under the GPL-3 license, and it is freely available through CRAN (https://cran.r-project.org/package=ggVennDiagram).

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Section: Resultsmentioning

confidence: 99%

“…Furthermore, Maguire et al (2020) used ggVennDiagram to confirm that their novel method has low bias and is more sensitive than three other methods for small RNA library preparation. In addition, ggVennDiagram is also used for analyzing the differences between several spatially varied oral metabolomics samples (Ciurli et al, 2021) and for comparing FIGURE 4 | Plots generated by the tools listed in Table 1. The used tools are ggVennDiagram, VennDiagram, colorfulVennPlot, venn, nVennR, eulerr, RVenn, gplots, interactiVenn, and Venny (A-K), respectively.…”

Section: Integration Of Ggvenndiagram Into Bioinformatics Analysis Pipelinesmentioning

confidence: 99%

ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

2021

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“…Sugi® Eyespear (blunt tip) is the swab selected for a spatially resolved sampling of saliva. The choice has been made after a careful and systemic evaluation, where Sugi® Eyespear has shown a reproducible volume recovery, low background contamination as well as the high coverage and reproducible molecular feature recoveries ( Ciurli et al., 2021 ).…”

Section: Before You Beginmentioning

confidence: 99%

“…For the human oral cavity, we provide an easy, flexible, and reproducible solution to comprehensively map the highly heterogeneous environment and elucidate the functionality of salivary components. For complete details on the use and execution of this protocol, please refer to Ciurli et al. (2021) .…”

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confidence: 99%

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Spatially resolved sampling of the human oral cavity for metabolic profiling

et al. 2021

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Summary Here, we present a spatially resolved sampling protocol for the oral human cavity aimed at untargeted metabolomics. We describe the spatial collection of salivary biospecimens, their preparation, and subsequent mass-spectrometry-based untargeted metabolomics analysis. Our protocol avoids complex procedures generally required for gland-specific saliva collection. For the human oral cavity, we provide an easy, flexible, and reproducible solution to comprehensively map the highly heterogeneous environment and elucidate the functionality of salivary components. For complete details on the use and execution of this protocol, please refer to Ciurli et al. (2021) .

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Spatially and temporally resolved metabolome of the human oral cavity

Ciurli,

Mohammed,

Ammon

et al. 2024

iScience

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Spatially resolved sampling for untargeted metabolomics: A new tool for salivomics

Abstract: Systematic evaluation of collection devices for untargeted metabolomics of salivaSpatially resolved sampling of saliva in the human oral cavity Enabling location-specific oral metabolomics

Cited by 6 publications

References 27 publications

ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

ggVennDiagram: An Intuitive, Easy-to-Use, and Highly Customizable R Package to Generate Venn Diagram

Spatially resolved sampling of the human oral cavity for metabolic profiling

Spatially and temporally resolved metabolome of the human oral cavity

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