Evidence map›Paper›PMID 37527009›Full record

ArticleBioinformatics (Oxford, England)2023

ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization.

Chen Yang, Jiahao Mai, Xuan Cao, Aaron Burberry, Fabio Cominelli, Liangliang Zhang

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 158 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
158citing papers in PubMed, 3 pooled it
–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

158 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Worldwide research trends on theFrontiers in immunology · 2026
    Pooled it
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  4. Gut microbes · 2026
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  15. Insights into the food safety implications of a commercialApplied and environmental microbiology · 2026
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  19. Article
  20. Article

98 more citing papers are in PubMed but not listed here.

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.

Chen YangDepartment of Biostatistics, Southern Medical University, Guangzhou 510515, China.ORCID 0009-0009-9151-2901
Jiahao MaiDepartment of Biostatistics, Southern Medical University, Guangzhou 510515, China.
Xuan CaoDepartment of Mathematical Sciences, University of Cincinnati, Cincinnati, OH 45221, United States.
Aaron BurberryDepartment of Pathology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States.
Fabio CominelliDepartment of Pathology, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, United States.ORCID 0000-0002-1571-1548
Liangliang ZhangDepartment of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, United States.ORCID 0000-0001-5986-2260

Funding

Translational and Therapeutics CoreP30AG072959 · NIA · CLEVELAND CLINIC LERNER COM-CWRU · PI Mark J Lowe · 2021 to 2026
$23.9M
The Cleveland Digestive Diseases Research Core Center (DDRCC)P30DK097948 · NIDDK · CASE WESTERN RESERVE UNIVERSITY · PI AMITABH CHAK · 2015 to 2026
$15.6M
CYTOKINES AND INFLAMMATORY BOWEL DISEASER01DK042191 · NIDDK · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI COMINELLI, FABIO, PIZARRO, THERESA TORRES · 1995 to 2022
$4.7M
NIA NIH HHS P30 AG072959NIDDK NIH HHS R01 DK042191
6 · The paper itself

Abstract

summaryMicrobiome research is now moving beyond the compositional analysis of microbial taxa in a sample. Increasing evidence from large human microbiome studies suggests that functional consequences of changes in the intestinal microbiome may provide more power for studying their impact on inflammation and immune responses. Although 16S rRNA analysis is one of the most popular and a cost-effective method to profile the microbial compositions, marker-gene sequencing cannot provide direct information about the functional genes that are present in the genomes of community members. Bioinformatic tools have been developed to predict microbiome function with 16S rRNA gene data. Among them, PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) has become one of the most popular functional profile prediction tools, which generates community-wide pathway abundances. However, no state-of-art inference tools are available to test the differences in pathway abundances between comparison groups. We have developed ggpicrust2, an R package, for analyzing functional profiles derived from 16S rRNA sequencing. This powerful tool enables researchers to conduct extensive differential abundance analyses and generate visually appealing visualizations that effectively highlight functional signals. With ggpicrust2, users can obtain publishable results and gain deeper insights into the functional composition of their microbial communities. AVAILABILITY AND IMPLEMENTATION: The package is open-source under the MIT and file license and is available at CRAN and https://github.com/cafferychen777/ggpicrust2. Its shiny web is available at https://a95dps-caffery-chen.shinyapps.io/ggpicrust2_shiny/.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaHumansPhylogenyRNA, Ribosomal, 16SSoftwareRNA, Ribosomal, 16S

Identifiers

PMID37527009
PMCPMC10425198

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.