scispace - formally typeset
Open AccessJournal ArticleDOI

phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.

Paul J. McMurdie, +1 more
- 22 Apr 2013 - 
- Vol. 8, Iss: 4
TLDR
The phyloseq project for R is a new open-source software package dedicated to the object-oriented representation and analysis of microbiome census data in R, which supports importing data from a variety of common formats, as well as many analysis techniques.
Abstract
Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

Evan Bolyen, +123 more
- 01 Aug 2019 - 
TL;DR: QIIME 2 development was primarily funded by NSF Awards 1565100 to J.G.C. and R.K.P. and partial support was also provided by the following: grants NIH U54CA143925 and U54MD012388.
Journal ArticleDOI

ggtree: an R package for visualization and annotation of phylogenetic trees with their covariates and other associated data

TL;DR: An r package, ggtree, which provides programmable visualization and annotation of phylogenetic trees, which can read more tree file formats than other softwares, and support visualization of phylo, multiphylo, phylo4, phyla4d, obkdata and phyloseq tree objects defined in other r packages.
Journal ArticleDOI

Waste not, want not: why rarefying microbiome data is inadmissible.

TL;DR: It is advocated that investigators avoid rarefying altogether and supported statistical theory is provided that simultaneously accounts for library size differences and biological variability using an appropriate mixture model.
Journal ArticleDOI

Microbiome Datasets Are Compositional: And This Is Not Optional.

TL;DR: The purpose of this review is to alert investigators to the dangers inherent in ignoring the compositional nature of the data, and point out that HTS datasets derived from microbiome studies can and should be treated as compositions at all stages of analysis.
Journal ArticleDOI

Human gut microbes impact host serum metabolome and insulin sensitivity

TL;DR: It is shown how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals and suggested that microbial targets may have the potential to diminish insulin resistance and reduce the incidence of common metabolic and cardiovascular disorders.
References
More filters
Journal Article

R: A language and environment for statistical computing.

R Core Team
- 01 Jan 2014 - 
TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
Book

ggplot2: Elegant Graphics for Data Analysis

TL;DR: This book describes ggplot2, a new data visualization package for R that uses the insights from Leland Wilkisons Grammar of Graphics to create a powerful and flexible system for creating data graphics.
Related Papers (5)