Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Modern Molecular Taxonomy01:29

Modern Molecular Taxonomy

74
Advancements in molecular biology have revolutionized the identification and characterization of bacteria, with multiple methods leveraging DNA sequencing for enhanced precision. As sequencing technologies improve and costs decline, these approaches are increasingly used in clinical, environmental, and evolutionary studies.Multilocus Sequence Typing (MLST) examines several housekeeping genes, essential chromosomal genes encoding cellular functions, to distinguish strains. Approximately...
74
Applications of Molecular Taxonomy01:20

Applications of Molecular Taxonomy

54
Molecular taxonomy has revolutionized the understanding and classification of bacteria, providing precise insights into their diversity, evolutionary relationships, and ecological roles. By utilizing molecular techniques such as DNA sequencing and fingerprinting, researchers have made significant strides in various fields related to bacterial studies.Resolving Taxonomic AmbiguitiesMolecular taxonomy has been instrumental in distinguishing closely related bacterial species initially thought to...
54

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Microbiota, Gender-Affirming Hormone Therapy, and Inflammatory Biomarkers in Transgender Women with HIV: Potential Implications for Cardiovascular Disease.

Transgender health·2026
Same author

Topological Data Analysis of Spatial Protein Expression in Multiplexed Spatial Proteomics Studies.

bioRxiv : the preprint server for biology·2026
Same author

A mixed effect similarity matrix regression model (SMRmix) for integrating multiple microbiome datasets at the community level.

Biometrics·2026
Same author

Cellular neighborhoods govern antitumor T-cell infiltration following anti-CTLA-4 in melanoma with primary resistance to anti-PD-1.

Cancer discovery·2026
Same author

Multiomics-guided discovery of protective microbiome signatures in lupus-prone mice treated with Faecalibacterium prausnitzii.

Nature communications·2026
Same author

DTH: a nonparametric test for homogeneity of multivariate dispersions.

Bioinformatics (Oxford, England)·2026
Same journal

OpenIMC: an open-source platform for analyzing single-cell and spatial proteomics by imaging mass cytometry.

BMC bioinformatics·2026
Same journal

NAP: an open source pipeline for cross-domain microbiome profiling using Nanopore sequencing-derived amplicon data.

BMC bioinformatics·2026
Same journal

SurvGME: an R package for survival analysis with graphical and measurement error models.

BMC bioinformatics·2026
Same journal

SimMapNet: a Bayesian framework for gene regulatory network inference using gene ontology similarities as external hint.

BMC bioinformatics·2026
Same journal

Dual channel drug-drug interactions extraction based on cross attention.

BMC bioinformatics·2026
Same journal

FeSseqdb: a curated sequence-level database and interpretable machine learning framework for identifying iron-sulfur proteins.

BMC bioinformatics·2026
See all related articles

Related Experiment Video

Updated: Aug 13, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

3.8K

Accommodating multiple potential normalizations in microbiome associations studies.

Hoseung Song1, Wodan Ling1, Ni Zhao2

  • 1Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.

BMC Bioinformatics
|January 19, 2023
PubMed
Summary
This summary is machine-generated.

Identifying microbial species differences is key for disease research. A new omnibus test combines multiple normalization methods, offering robust results without needing to select the best one.

Keywords:
Cauchy combination testDifferent library sizeNormalizationOmnibus approach

More Related Videos

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
08:05

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Published on: March 19, 2018

19.8K
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.8K

Related Experiment Videos

Last Updated: Aug 13, 2025

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
08:27

Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

Published on: July 27, 2021

3.8K
Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing
08:05

Guided Protocol for Fecal Microbial Characterization by 16S rRNA-Amplicon Sequencing

Published on: March 19, 2018

19.8K
Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
11:22

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

28.8K

Area of Science:

  • Microbiome research
  • Statistical bioinformatics
  • Disease association studies

Background:

  • Microbial communities are linked to diseases like obesity and HIV.
  • Differential abundance analysis requires careful normalization due to data complexities (zero-inflation, over-dispersion).
  • Existing normalization methods present challenges in optimizing the detection of true biological signals.

Purpose of the Study:

  • To develop a robust method for identifying differentially abundant microbial species.
  • To overcome the limitations of selecting a single optimal normalization strategy.
  • To provide a powerful and flexible approach for microbiome data analysis.

Main Methods:

  • Proposed an omnibus approach based on a Cauchy combination test.
  • Aggregated p-values from individual normalization strategies to enhance power.
  • Incorporated a truncated test statistic to mitigate power loss.
  • Compared the omnibus approach against individual normalization methods using regression and association tests.

Main Results:

  • The omnibus approach demonstrated power comparable to the best individual normalization strategy across various simulation settings.
  • The proposed method effectively controlled the type I error rate.
  • Performance remained robust regardless of simulation parameters.

Conclusions:

  • The omnibus test simplifies differential abundance analysis by eliminating the need for manual selection of normalization methods.
  • This aggregated approach offers powerful results, approximating the performance of the optimal normalization strategy.
  • It provides a reliable alternative to potentially suboptimal individual normalization choices, enhancing research reproducibility.