analyseOtu: Analysis of OTU count data

In ebimetagenomics: EBI Metagenomics Portal

Description

This function takes as input a data frame representing OTU counts, such as returned by getRunOtu, and conducts a range of analyses relating to taxa diversity and coverage estimation.

Usage

analyseOtu(otu, plot = TRUE)

Arguments

otu	An OTU data frame.
plot	If TRUE, calls plotOtu to generate a plot.

Value

The function returns a numeric vector with named elements representing the results of various analyses. As well as computing various different estimates of the total number of taxa in the community that was sampled, it also computes estimates (assuming a Poisson-log-normal TAD) of the number of sequences required in order to observe a given fraction of the total species present. This can be useful for estimating required sequencing effort. Several of the fields should be familiar from the vegan function estimateR. The breakaway estimate has also been included. S.vln is Preston's veiled log-normal method and S.pln is an estimate from a Poisson-log-Normal SAD fit. Under the same assumption of an underlying Poisson-log-Normal species abundance distribution (and using the same fit), N.75, N.90, N.95 and N.99 are estimates of the N.obs required in order to obtain 75%, 90%, 95% and 99% species coverage in a future sample.

See Also

getSampleOtu, getRunOtu, plotOtu

Examples

ps=getProjectSummary("SRP047083")
samp=projectSamples(ps)
runs=runsBySample(ps,samp[2])
otu=getRunOtu(runs[1])
analyseOtu(otu,plot=FALSE)

ebimetagenomics documentation built on May 2, 2019, 5 p.m.