doc: Dissimilarity-Overlap Curve (DOC)

In hallucigenia-sparsa/seqtime: Time Series Analysis of Sequencing Data

Dissimilarity-Overlap Curve (DOC)

Description

Given matrix of relative taxon abundances, plot the dissimilarity-overlap curve (DOC) sample-wise. The DOC method was developed by Bashan and colleagues.

Usage

doc(x, B = 100, polygons = FALSE, rand = FALSE, lower.conf = 0.03,
  upper.conf = 0.97, null.model = "assembly", doc.res = NULL)

Arguments

x	rows are taxa, columns are samples, abundance in each sample is assumed to sum to one
B	bootstrap iterations, if set to 0 or below, no bootstraps are carried out
polygons	draw a polygon instead of the lower and upper confidence line (in development)
rand	randomize the data sample-wise before starting the DOC analysis
lower.conf	lower limit of the confidence interval
upper.conf	upper limit of the confidence interval
null.model	the null model to use, permut shuffles x sample-wise, assembly selects for each non-zero taxon one of the values taken across the samples at random
doc.res	the result of a previous run of the doc method is added in green with black points, current result is shown in red with grey points (to plot null model together with data)

Value

a list with the overlaps, dissimilarities, lowess smoothed overlaps and dissimilarites and lower and upper confidence intervals

References

A. Bashan et al. (2016). Universality of human microbial dynamics, Nature 534, 259-262.

Examples

## Not run: 
data("david_stoolA_otus")
data=normalize(rarefyFilter(david_stoolA_otus,min=10000)[[1]])
doc.out=doc(data[,1:50],B=10) # apply the DOC method to the first 50 samples
# plot the DOC curve together with the curve for the null model
doc.null=doc(data[,1:50],B=10,rand=TRUE,doc.res=doc.out)

## End(Not run)

hallucigenia-sparsa/seqtime documentation built on Jan. 9, 2023, 11:53 p.m.