Like in paper https://www.pnas.org/content/111/16/5980 (Fig. 4).
inc_overlap(.data, .fun, .step = 1000, .n.steps = 10, .downsample = F, .bootstrap = NA, .verbose.inc = T, ...)
.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 |
.downsample | If T 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 |