DiversityCurve-class - S4 class defining a diversity curve

## Description¶

`DiversityCurve` defines diversity (`D`) scores over multiple diversity orders (`Q`).

## Usage¶

``````"print"(x)
``````
``````"plot"(x, y, ...)
``````
``````"plot"(x, y, ...)
``````

## Arguments¶

x
DiversityCurve object
y
diversity order to plot (q).
arguments to pass to plotDiversityCurve or plotDiversityTest.

## Slots¶

`diversity`
data.frame defining the diversity curve with the following columns:
• `group`: group label.
• `q`: diversity order.
• `d`: mean diversity index over all bootstrap realizations.
• `d_sd`: standard deviation of the diversity index over all bootstrap realizations.
• `d_lower`: diversity lower confidence inverval bound.
• `d_upper`: diversity upper confidence interval bound.
• `e`: evenness index calculated as `D` divided by `D` at `Q=0`.
• `e_lower`: evenness lower confidence inverval bound.
• `e_upper`: eveness upper confidence interval bound.
`tests`
data.frame describing the significance test results with columns:
• `test`: string listing the two groups tested.
• `delta_mean`: mean of the `D` bootstrap delta distribution for the test.
• `delta_sd`: standard deviation of the `D` bootstrap delta distribution for the test.
• `pvalue`: p-value for the test.
`group_by`
string specifying the name of the grouping column in diversity calculation.
`groups`
vector specifying the names of unique groups in group column in diversity calculation.
`method`
string specifying the type of diversity calculated.
`q`
vector of diversity hill diversity indices used for computing diversity.
`n`
numeric vector indication the number of sequences sampled in each group.
`ci`
confidence interval defining the upper and lower bounds (a value between 0 and 1).