R: Visualise diversity.

vis.immunr_chao1 {immunarch} | R Documentation

## Visualise diversity.

### Description

An utility function to visualise the output from `repDiversity`.

### Usage

    ## S3 method for class 'immunr_chao1'
    vis(
      .data,
      .by = NA,
      .meta = NA,
      .errorbars = c(0.025, 0.975),
      .errorbars.off = FALSE,
      .points = TRUE,
      .test = TRUE,
      .signif.label.size = 3.5,
      ...
    )

### Arguments

`.data` | Output from `repDiversity`.
`.by` | Pass NA if you want to plot samples without grouping. You can pass a character vector with one or several column names from ".meta" to group your data before plotting. In this case you should provide ".meta". You can pass a character vector that exactly matches the number of samples in your data, each value should correspond to a sample's property. It will be used to group data based on the values provided. Note that in this case you should pass NA to ".meta".
`.meta` | A metadata object. An R dataframe with sample names and their properties, such as age, serostatus or hla.
`.errorbars` | A numeric vector of length two with quantiles for error bars on sectors. Disabled if ".errorbars.off" is TRUE.
`.errorbars.off` | If TRUE then plot CI bars for distances between each group. Disabled if no group passed to the ".by" argument.
`.points` | A logical value defining whether points will be visualised or not.
`.test` | A logical vector whether statistical tests should be applied. See "Details" for more information.
`.signif.label.size` | An integer value defining the size of text for p-value.
`...` | Not used here.

### Details

If data is grouped, then statistical tests for comparing means of groups will be performed, unless `.test = FALSE` is supplied. In case there are only two groups, the Wilcoxon rank sum test (https://en.wikipedia.org/wiki/Wilcoxon_signed-rank_test) is performed (R function `wilcox.test` with an argument `exact = FALSE`) for testing if there is a difference in mean rank values between two groups. In case there more than two groups, the Kruskal-Wallis test (https://en.wikipedia.org/wiki/Kruskal A significant Kruskal-Wallis test indicates that at least one sample stochastically dominates one other sample. Adjusted for multiple comparisons P-values are plotted on the top of groups. P-value adjusting is done using the Holm method (https://en.wikipedia.org/wiki/Holm You can execute the command `?p.adjust` in the R console to see more.

### Value

A ggplot2 object.

### See Also

repDiversity vis

### Examples

    data(immdata)
    dv <- repDiversity(immdata$data, "chao1")
    vis(dv)

[Package immunarch version 0.6.5 Index]