2023
DOI: 10.1093/bioinformatics/btad470
|View full text |Cite
|
Sign up to set email alerts
|

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

Abstract: Summary Microbiome 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 inf… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
10
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
7
2

Relationship

0
9

Authors

Journals

citations
Cited by 53 publications
(20 citation statements)
references
References 30 publications
(33 reference statements)
0
10
0
Order By: Relevance
“… 107 Functional abundances were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) 108 and visualized using the R package ggpicrust2. 109 16S sequencing data were deposited in the NCBI BioProject: PRJNA900580.…”
Section: Methodsmentioning
confidence: 99%
“… 107 Functional abundances were predicted using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) 108 and visualized using the R package ggpicrust2. 109 16S sequencing data were deposited in the NCBI BioProject: PRJNA900580.…”
Section: Methodsmentioning
confidence: 99%
“…The functional genes were then mapped to their respective KO functions (KEGG level 4 classification unit) and the associated KEGG pathway (KEGG level 3 classification unit). We used the ggpicrust2 package (v1.7.2) for statistical analysis and visualization after obtaining the community functional abundance table (Yang et al., 2023).…”
Section: Methodsmentioning
confidence: 99%
“…MetaCyc functional pathways and associated abundance were inferred from EC number abundances 96 . Differential abundance testing of functional pathways between tolerant and non-tolerant mice was analyzed and visualized using the R package ggpicrust2 (v1.7.3) 97 .…”
Section: Methodsmentioning
confidence: 99%