Demo Data from EDBT 2026 / reviewers in the wild / expert
Fabio Cominelli
dblp:370/5748
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-1571-1548ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › computational microbiology › microbiome analysis
differential abundance testing |
0.7 | 1 | 2023 | ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization · Bioinform. 2023 |
Bioinformatics and computational biology › computational microbiology
microbiome analysis |
0.7 | 1 | 2023 | ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualization · Bioinform. 2023 |
Methods — techniques the papers use, named apart from their topics
statistical testing · 0.7PICRUSt2 · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | ggpicrust2: an R package for PICRUSt2 predicted functional profile analysis and visualizationabstractSUMMARY: 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 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/. Jiahao Mai, Xuan Cao, Aaron Burberry, Fabio Cominelli |
Bioinform. | 5 |