Evidence map›Paper›PMID 35913976›Full record

ArticlePloS one2022

MiCloud: A unified web platform for comprehensive microbiome data analysis.

Won Gu, Jeongsup Moon, Crispen Chisina, Byungkon Kang, Taesung Park, Hyunwook Koh

Abstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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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

6 authors.

Won GuDepartment of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Jeongsup MoonInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.ORCID 0000-0002-5118-0895
Crispen ChisinaDepartment of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.
Byungkon KangDepartment of Computer Science, The State University of New York, Korea, Incheon, South Korea.
Taesung ParkInterdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
Hyunwook KohDepartment of Applied Mathematics and Statistics, The State University of New York, Korea, Incheon, South Korea.ORCID 0000-0001-6893-7164

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent advance in massively parallel sequencing has enabled accurate microbiome profiling at a dramatically lowered cost. Then, the human microbiome has been the subject of intensive investigation in public health and medicine. In the meanwhile, researchers have developed lots of microbiome data analysis methods, protocols, and/or tools. Among those, especially, the web platforms can be highlighted because of the user-friendly interfaces and streamlined protocols for a long sequence of analytic procedures. However, existing web platforms can handle only a categorical trait of interest, cross-sectional study design, and the analysis with no covariate adjustment. We therefore introduce here a unified web platform, named MiCloud, for a binary or continuous trait of interest, cross-sectional or longitudinal/family-based study design, and with or without covariate adjustment. MiCloud handles all such types of analyses for both ecological measures (i.e., alpha and beta diversity indices) and microbial taxa in relative abundance on different taxonomic levels (i.e., phylum, class, order, family, genus and species). Importantly, MiCloud also provides a unified analytic protocol that streamlines data inputs, quality controls, data transformations, statistical methods and visualizations with vastly extended utility and flexibility that are suited to microbiome data analysis. We illustrate the use of MiCloud through the United Kingdom twin study on the association between gut microbiome and body mass index adjusting for age. MiCloud can be implemented on either the web server (http://micloud.kr) or the user's computer (https://github.com/wg99526/micloudgit).

Indexed as

Gastrointestinal MicrobiomeMicrobiotaCross-Sectional StudiesData AnalysisHigh-Throughput Nucleotide SequencingHumans

Identifiers

PMID35913976
PMCPMC9342768

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LicenceCC BY
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Registered trials

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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.