DiversityCurve-class {alakazam} R Documentation

## S4 class defining a diversity curve

### Description

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

### Usage

```## S4 method for signature 'DiversityCurve'
print(x)

## S4 method for signature 'DiversityCurve,missing'
plot(x, y, ...)

## S4 method for signature 'DiversityCurve,numeric'
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).

[Package alakazam version 1.1.0 Index]