inc_overlap: Incremental counting of repertoire similarity

In abrown435/immunarch-test: Bioinformatics Analysis of T-Cell and B-Cell Immune Repertoires

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)

abrown435/immunarch-test documentation built on July 29, 2020, 12:04 a.m.