theseus (version 0.1.0)

prev: Create prevalence vs abundance plot

Description

Function 'prev' (prevalence plot) tabulates the prevalence and abundance of each taxa in a phyloseq object and plots the results as a ggplot object. This may assist the user in determining what filtering and preprocessing steps should be taken regarding the removal of low count taxa.

Usage

prev(PS, taxon, n_taxa = 10, abund_threshold = 3,
  prev_threshold = ceiling(0.05 * phyloseq::nsamples(PS)))

Arguments

PS

(required) A phyloseq object.

taxon

Taxonomic level to be displayed. Defaults to 'Phylum'.

n_taxa

The number of taxa to display at the given 'taxon' level. The most abundant taxa at that group are selected. Defaults to 10.

abund_threshold

User selected value for the lowest acceptable total abundance. Defaults to 3.

prev_threshold

User selected value for the lowest acceptable prevalence. Defaults to 5 rounded up to the nearest integer.

Value

A ggplot object.

Details

Low count taxa are often filtered from OTU tables to reduce possible error or noise. Examination of the raw (unfiltered) OTU table should be carried out to ensure that appropriate thresholds for prevalence (number of samples a taxa was observed in) and abundance (the total number of times a taxa was observed) are being selected. Function 'prev' plots each taxa according to thier prevalence and abundance within the dataset.

References

Callahan BJ, Sankaran K, Fukuyama JA et al. Bioconductor Workflow for Microbiome Data Analysis: from raw reads to community analyses. F1000Research 2016, 5:1492 (doi: 10.12688/f1000research.8986.2) Perraudeau F, Risso D, Street K et al. Bioconductor workflow for single-cell RNA sequencing: Normalization, dimensionality reduction, clustering, and lineage inference. F1000Research 2017, 6:1158 (doi:10.12688/f1000research.12122.1)

Examples

# NOT RUN {
library(theseus)
data('WWTP_Impact')
p.prev <- prev(WWTP_Impact, taxon="Phylum", n_taxa=10)
p.prev
# }
# NOT RUN {
# }