Evidence map›Paper›PMID 33225342›Full record

ArticleBioinformatics (Oxford, England)2021

MiRKAT: kernel machine regression-based global association tests for the microbiome.

Nehemiah Wilson, Ni Zhao, Xiang Zhan, Hyunwook Koh, Weijia Fu, Jun Chen, Hongzhe Li, Michael C Wu, Anna M Plantinga

Registry-linked trialAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05009758 (Moving Towards PREcision Medicine In United Airways Disease), which is not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05009758 narecruitingnot on this map

Moving Towards PREcision Medicine In United Airways Disease: Unraveling inflaMmatory Patterns in Asthmatic Patients With or Without Nasal Polyps (PREMIUM) - a Descriptive Pilot Study

TypeinterventionalSponsorMedical University of ViennaRan2021 to 2026Enrolled30ConditionsAsthma, Chronic Rhinosinusitis With Nasal Polyps, Chronic Rhinosinusitis (Diagnosis), Nasal PolypsArmsBlood sampling, Nasosorption, Oral sampling, Bronchoscopy, Nasal biopsy
3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Trial
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  11. Analysis of Microbiome Data.Annual review of statistics and its application · 2024
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Bioinformatic and Statistical Analysis of Microbiome Data.Methods in molecular biology (Clifton, N.J.) · 2023
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Nehemiah WilsonDepartment of Mathematics and Statistics, Williams College, Williamstown, MA 01267, USA.
Ni ZhaoDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA.ORCID 0000-0002-7762-3949
Xiang ZhanDepartment of Public Health Sciences, Penn State College of Medicine, Hershey, PA 17033, USA.
Hyunwook KohDepartment of Applied Mathematics and Statistics, The State University of New York, Korea (SUNY Korea), Incheon 21985, South Korea.
Weijia FuInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA 98121, USA.
Jun ChenDivision of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA.
Hongzhe LiDepartment of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Michael C WuPublic Health Sciences Division, Biostatistics and Biomathematics Program, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.ORCID 0000-0002-3357-6570
Anna M PlantingaDepartment of Mathematics and Statistics, Williams College, Williamstown, MA 01267, USA.

Funding

Joint Analysis of Microbiome and Other Genomic Data TypesR01GM129512 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI WU, MICHAEL CHIAO-AN · 2018 to 2021
$1.6M
Novel statistical methods for controlled variable selection of microbiome dataR21AI144765 · NIAID · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI CHINCHILLI, VERNON M · 2020 to 2021
$412k
National Science Foundation 1953189NIAID NIH HHS R21 AI144765NIGMS NIH HHS R01 GM129512
6 · The paper itself

Abstract

summaryDistance-based tests of microbiome beta diversity are an integral part of many microbiome analyses. MiRKAT enables distance-based association testing with a wide variety of outcome types, including continuous, binary, censored time-to-event, multivariate, correlated and high-dimensional outcomes. Omnibus tests allow simultaneous consideration of multiple distance and dissimilarity measures, providing higher power across a range of simulation scenarios. Two measures of effect size, a modified R-squared coefficient and a kernel RV coefficient, are incorporated to allow comparison of effect sizes across multiple kernels. AVAILABILITY AND IMPLEMENTATION: MiRKAT is available on CRAN as an R package. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

MicrobiotaComputer SimulationSoftware

Identifiers

PMID33225342
PMCPMC8495888

What OpenQuestion holds

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Read underepoch 390

Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.