potential_analysis {microbiome} | R Documentation

## Bootstrapped Potential Analysis

### Description

Analysis of multimodality based on bootstrapped potential analysis of Livina et al. (2010) as described in Lahti et al. (2014).

### Usage

    potential_analysis(x, peak.threshold = 0, bw.adjust = 1,
      bs.iter = 100, min.density = 1)

### Arguments

`x` | Input data vector
`peak.threshold` | Mode detection threshold
`bw.adjust` | Bandwidth adjustment
`bs.iter` | Bootstrap iterations
`min.density` | minimum accepted density for a maximum; as a multiple of kernel height

### Value

List with following elements:

- modesNumber of modes for the input data vector (the most frequent number of modes from bootstrap)

- minimaAverage of potential minima across the bootstrap samples (for the most frequent number of modes)

- maximaAverage of potential maxima across the bootstrap samples (for the most frequent number of modes)

- unimodality.supportFraction of bootstrap samples exhibiting unimodality

- bwsBandwidths

### References

- Livina et al. (2010). Potential analysis reveals changing number of climate states during the last 60 kyr. Climate of the Past, 6, 77-82.

- Lahti et al. (2014). Tipping elements of the human intestinal ecosystem. Nature Communications 5:4344.

### See Also

plot_potential

### Examples

    # Example data; see help(peerj32) for details
    data(peerj32)

    # Log10 abundance of Dialister
    x <- abundances(transform(peerj32$phyloseq, "clr"))['Dialister',]

    # Bootstrapped potential analysis
    # In practice, use more bootstrap iterations
    res <- potential_analysis(x, peak.threshold=0, bw.adjust=1,
        bs.iter=9, min.density=1)

[Package microbiome version 1.6.0 Index]