R: Incremental counting of repertoire similarity

inc_overlap {immunarch} | R Documentation

## Incremental counting of repertoire similarity

### Description

Like in paper https://www.pnas.org/content/111/16/5980 (Fig. 4).

### Usage

    inc_overlap(
      .data,
      .fun,
      .step = 1000,
      .n.steps = 10,
      .downsample = FALSE,
      .bootstrap = NA,
      .verbose.inc = TRUE,
      ...
    )

### Arguments

`.data` | The data to be processed. Can be data.frame, data.table, or a list of these objects. Every object must have columns in the immunarch compatible format. immunarch_data_format Competent users may provide advanced data representations: DBI database connections, Apache Spark DataFrame from copy_to or a list of these objects. They are supported with the same limitations as basic objects. Note: each connection must represent a separate repertoire.
`.fun` | Function to compute overlaps. e.g., `morisita_index`.
`.step` | Either an integer or a numeric vector. In the first case, the integer defines the step of incremental overlap. In the second case, the vector encodes all repertoire sampling depths.
`.n.steps` | Integer. Number of steps if `.step` is a single integer. Skipped if ".step" is a numeric vector.
`.downsample` | If TRUE then perform downsampling to N clonotypes at each step instead of choosing the top N clonotypes.
`.bootstrap` | Pass NA to turn off any bootstrapping, pass a number to perform bootstrapping with this number of tries.
`.verbose.inc` | Logical. If TRUE then show output from the computation process.
`...` | Other arguments passed to `.fun`.

### Value

List with overlap matrices.

### Examples

    data(immdata)
    ov <- repOverlap(immdata$data, "inc+overlap", .step = 100, .verbose.inc = FALSE, .verbose = FALSE)
    vis(ov)

[Package immunarch version 0.6.7 Index]