DiversityCurve-class {alakazam}

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).