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VALENCIA: A Nearest Centroid Classification Method for Vaginal Microbial Communities Based on Composition
Jacques Ravel
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD USA.
Corresponding Author
ORCiD: https://orcid.org/0000-0002-0851-2233
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Microbiome.
Background
Taxonomic profiles of vaginal microbial communities can be sorted into a discrete number of categories termed Community State Types (CSTs). This approach is advantageous because collapsing a hyper dimensional taxonomic profile into a single categorical variable enables efforts such as data exploration, epidemiological studies and statistical modeling. Vaginal communities are typically assigned to CSTs based on the results of hierarchical clustering of the pairwise distances between samples. However, this approach is problematic because it complicates between-study comparisons and because the results are entirely dependent on the particular set of samples that were analyzed. We sought to standardize and advance the assignment of samples to CSTs.
Results
We developed VALENCIA (VAginaL community state typE Nearest CentroId clAssifier), a nearest centroid based tool which classifies samples based on their similarity to a set of reference centroids. The references were defined using a comprehensive set of 13,160 taxonomic profiles from 1,975 women in the United States. This large dataset allowed us to comprehensively identify, define, and characterize vaginal CSTs common to reproductive age women, and expand upon the CSTs that had been defined in previous studies. We validated the broad applicability of VALENCIA for the classification of vaginal microbial communities by using it to classify three test datasets which included reproductive age eastern and southern African women, adolescent girls, and a racially/ethnically and geographically diverse sample of postmenopausal women. VALENCIA performed well on all three datasets despite the substantial variations in sequencing strategies and bioinformatics pipelines, indicating its broad application to vaginal microbiota. We further describe the relationships between community characteristics (vaginal pH, Nugent score) and participant demographics (race, age) and the CSTs defined by VALENCIA.
Conclusion
VALENCIA provides a much-needed solution for the robust and reproducible assignment of vaginal community state types. This will allow unbiased analysis of both small and large vaginal microbiota datasets, comparisons between datasets and meta-analyses that combine multiple datasets.
Keywords
Community State Types (CSTs), VALENCIA (VAginaL community state typE Nearest CentroId clAssifier), large vaginal microbiota datasets
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This is a list of supplementary files associated with this preprint. Click to download.
- SupplementalTable1.xlsx
- SupplementalFigure2.pdf
Supplemental Figure 2: Odds of women with each sub-CST having a vaginal pH >4.5.
- SupplementalFigure1.pdf
Supplemental Figure 1: Illustration of cluster selection for construction of VALENCIA sub-CST centroids. Stretched version of dendrogram from Figure 1 with horizontal line indicating chosen cluster threshold (a). Subset heatmap and dendrogram of samples in CST IV-C (b). Hierarchical clustering was performed on this subset using Bray-Curtis dissimilarity with Ward linkage and the horizontal line indicating cluster threshold. Silhouette and Davies-Bouldin scores for a range of number of clusters (c). Horizontal lines indicate the values for the final 13 sub-CSTs, after sub-clustering the CST IV-C samples.
- AdditionalFile1.docx
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CURRENT STATUS: Published
Version 1
Posted 22 Sep, 2020
Published
On 23 Nov, 2020
No community comments so far
Editorial decision: Accept
On 01 Oct, 2020
First submitted
On 16 Sep, 2020
Editor assigned
On 16 Sep, 2020
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On 15 Sep, 2020
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On 15 Sep, 2020
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Subject Areas
General Microbiology
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This preprint is under consideration at Microbiome. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
VALENCIA: A Nearest Centroid Classification Method for Vaginal Microbial Communities Based on Composition
Jacques Ravel
Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD USA.
Corresponding Author
ORCiD: https://orcid.org/0000-0002-0851-2233
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
Version 1
Posted 22 Sep, 2020
Published
On 23 Nov, 2020
No community comments so far
Editorial decision: Accept
On 01 Oct, 2020
First submitted
On 16 Sep, 2020
Editor assigned
On 16 Sep, 2020
Submission checks complete
On 15 Sep, 2020
Editor invited
On 15 Sep, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
General Microbiology
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published version at Microbiome.
Background
Taxonomic profiles of vaginal microbial communities can be sorted into a discrete number of categories termed Community State Types (CSTs). This approach is advantageous because collapsing a hyper dimensional taxonomic profile into a single categorical variable enables efforts such as data exploration, epidemiological studies and statistical modeling. Vaginal communities are typically assigned to CSTs based on the results of hierarchical clustering of the pairwise distances between samples. However, this approach is problematic because it complicates between-study comparisons and because the results are entirely dependent on the particular set of samples that were analyzed. We sought to standardize and advance the assignment of samples to CSTs.
Results
We developed VALENCIA (VAginaL community state typE Nearest CentroId clAssifier), a nearest centroid based tool which classifies samples based on their similarity to a set of reference centroids. The references were defined using a comprehensive set of 13,160 taxonomic profiles from 1,975 women in the United States. This large dataset allowed us to comprehensively identify, define, and characterize vaginal CSTs common to reproductive age women, and expand upon the CSTs that had been defined in previous studies. We validated the broad applicability of VALENCIA for the classification of vaginal microbial communities by using it to classify three test datasets which included reproductive age eastern and southern African women, adolescent girls, and a racially/ethnically and geographically diverse sample of postmenopausal women. VALENCIA performed well on all three datasets despite the substantial variations in sequencing strategies and bioinformatics pipelines, indicating its broad application to vaginal microbiota. We further describe the relationships between community characteristics (vaginal pH, Nugent score) and participant demographics (race, age) and the CSTs defined by VALENCIA.
Conclusion
VALENCIA provides a much-needed solution for the robust and reproducible assignment of vaginal community state types. This will allow unbiased analysis of both small and large vaginal microbiota datasets, comparisons between datasets and meta-analyses that combine multiple datasets.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6