phyloseq
phyloseq provides an R-based framework for import, storage, analysis, and visualization of microbiome census data generated by DNA sequencing.
Key Features:
- Object-Oriented Representation: Uses an object-oriented data structure to represent and manage microbiome data within R.
- Data Import and Compatibility: Supports importing data from various common file formats for microbiome census datasets.
- Comprehensive Analysis Techniques: Implements calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, and ordination methods.
- Integration with R Packages: Interoperates with other R packages to apply additional analytical functions to its data structures.
- Visualization: Generates graphics for representation and interpretation of microbiome analyses.
Scientific Applications:
- Ecology: Enables analysis of ecological patterns in microbial communities.
- Genetics: Supports integration of genetic information in microbiome studies.
- Phylogenetics: Facilitates phylogenetic analyses, including Fast UniFrac comparisons.
- Multivariate Statistics: Supports multivariate statistical analyses and ordination methods for community data.
- Visualization and Testing: Provides visualization and statistical testing workflows for microbiome datasets.
Methodology:
Implements an object-oriented R data structure to import microbiome census data from common formats and perform calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination, and visualization while interoperating with other R packages.
Topics
Collections
Details
- License:
- GPL-3.0
- Tool Type:
- command-line tool, library
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- R
- Added:
- 1/17/2017
- Last Updated:
- 1/9/2019
Operations
Data Inputs & Outputs
Analysis
Publications
McMurdie PJ, Holmes S. phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data. PLoS ONE. 2013;8(4):e61217. doi:10.1371/journal.pone.0061217. PMID:23630581. PMCID:PMC3632530.