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phyloNEON

A set of tools in R and Python to run phylogenetic and taxonomic analyses on NEON and related data

Installation

To install phyloNEON, you will need the devtools package.

library(devtools)

install_github("NEONScience/phyloNEON/phyloNEON")

Accessing NEON data

The initial functions of phyloNEON were developed to allow for converting data downloaded from NEON into formats that can easily be imported into other programs. Additional functions will be added, so watch this space. The first example below is to convert Microbe Community Taxonomy data into formats for importing into the popular R package Phyloseq.

Importing NEON Microbe Community Taxonomy (MCT) data into phyloseq

This example uses basic functions of phyloNEON to convert data downloaded using neonUtilities. This will start with a smaller dataset. Due to the increased sequencing output of NEON microbial data, the user is encouraged to begin with small sets of data, and then build from there.

Download MCT data with neonUtilities

Make sure to set the package parameter to 'expanded' to download the perSample tables.

library(neonUtilities)

soil.mct <- loadByProduct(
  dpID='DP1.10081.002',
  startdate = "2021-01",
  enddate = "2021-12",
  package='expanded',
  site = c('BONA','HARV','NIWO'))

Create OTU frequency table

The createFreqTable function will convert the downloaded neonUtilities data to a phyloseq frequency table object

library(phyloNEON)

soil.mct.freq <- createFreqTable(soil.mct, gene = 'ITS', sampleType = 'soil')

Create taxa table

The createTaxTable function will convert the downloaded neonUtilities data to a phyloseq taxon table object

library(phyloNEON)


soil.mct.tax <- createTaxTable(soil.mct, gene = 'ITS',
                                sampleType = 'soil')


Create sample metadata table

This function will create a very basic metadata table that takes the information from the sample metadata table in the download. Additional metadata can be added (and watch this space for additional information and tutorials), but this function gives you the minimum to get started using Phyloseq.

library(phyloNEON)

soil.meta <- createMetaTable(soil.mct,gene='ITS',sampleType = 'soil')