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

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.

Documentation

Downloads

Links