normalizeAlphaDiv: Normalize Alpha Diversity Values for Plotting.

Description Usage Arguments Details Author(s) References Examples

Description

This function normalizes the alpha diversity values of a single patient's time course to the initial time point. The initial time point is used as 100 percent. This allows for plotting of multiple alpha diversity metrics on a single plot, despite differences in value magnitude.

Usage

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normalizeAlphaDiv(alpha.div.input,
	alpha.div.metric,
	subject.id.range,
	subject.id.col="SubjectID",
	tmpt.id.col="Time_point")

Arguments

alpha.div.input

The data.frame from Qiime containing the alpha diversity information for the dataset. This should also include subject ID and time point information.

alpha.div.metric

The name(s) of the columns containing the alpha diversity metric information to be used for normalization.

subject.id.range
subject.id.col

Name of the subject ID column found in alpha.div.input. Default is "SubjectID".

tmpt.id.col

Name of the time point column found in alpha.div.input. Default is "Time_point".

Details

Package: patPRO
Type: Package
Version: 1.0.0
Date: 2015-09-18
License: GPLv3

An overview of how to use the package, including the most important functions, is included in the supplemental R notebook patPROExampleWorkflow.html.

Author(s)

Geoffrey Hannigan <ghanni@upenn.edu>, Loesche MA, Hodkinson BP, Mehta S, Elizabeth Grice <egrice@upenn.edu>

References

patPRO: An R package for the visualization of longitudinal microbiome data. Hannigan GD, Loesche MA, Hodkinson BP, Mehta S, Grice EA.

Examples

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data("PatProAlphaDiv",package="patPRO")
data("PatProMap",package="patPRO")
mergedMapAlpha <- mergeMapMetaData(map.file=PatProMap, 
	merging.file=PatProAlphaDiv, 
	map.sub.id="SubjectID", 
	map.tmpt="Time_point", 
	map.smpl.id="SampleID", 
	sample.id.col="SampleID")
testNormAlphaDiv <- normalizeAlphaDiv(mergedMapAlpha, c("chao1","shannon"), 1)

Example output

No id variables; using all as measure variables

patPRO documentation built on May 1, 2019, 10:56 p.m.