Vaginal Microbiome Metagenome Inference Accuracy: Differential Measurement Error according to Community Composition-Reference-Cited by-同舟云学术

Vaginal Microbiome Metagenome Inference Accuracy: Differential Measurement Error according to Community Composition

Published:2023-04-27 Issue:2 Volume:8 Page:
ISSN:2379-5077
Container-title:mSystems
language:en
Short-container-title:mSystems

Author:

Carter Kayla A.¹^ORCID,Fodor Anthony A.²,Balkus Jennifer E.¹³,Zhang Angela⁴,Serrano Myrna G.⁵⁶,Buck Gregory A.⁵⁶⁷^ORCID,Engel Stephanie M.⁸,Wu Michael C.⁹,Sun Shan²

Affiliation:

1. Department of Epidemiology, University of Washington, Seattle, Washington, USA

2. Department of Bioinformatics and Genomics, University of North Carolina at Charlotte, Charlotte, North Carolina, USA

3. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

4. Department of Biostatistics, University of Washington, Seattle, Washington, USA

5. Department of Microbiology and Immunology, School of Medicine, Virginia Commonwealth University, Richmond, Virginia, USA

6. Center for Microbiome Engineering and Data Analysis, Virginia Commonwealth University, Richmond, Virginia, USA

7. Department of Computer Science, College of Engineering, Virginia Commonwealth University, Richmond, Virginia, USA

8. Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

9. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

Abstract

Compared to taxonomic composition, the functional potential within a bacterial community is more relevant to establishing mechanistic understandings and causal relationships between the microbiome and health outcomes. Metagenome inference attempts to bridge the gap between 16S rRNA gene amplicon sequencing and whole-metagenome sequencing by predicting a microbiome’s gene content based on its taxonomic composition and annotated genome sequences of its members.

Funder

NIH Division of Research Resources

HHS | NIH | Eunice Kennedy Shriver National Institute of Child Health and Human Development

HHS | NIH | National Institute of Allergy and Infectious Diseases

HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases

HHS | NIH | National Institute of Environmental Health Sciences

HHS | NIH | National Institute on Minority Health and Health Disparities

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

Link

https://journals.asm.org/doi/pdf/10.1128/msystems.01003-22

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