Number of iterations (i.e., size of a resulting distribution).
.size
Size of samples. For .sim == "uniform" stands for number of rows to take.
For .sim == "percentage" stands for number of barcodes / read counts to take.
.sim
A character string indicating the type of simulation required. Possible values are
"uniform" or "percentage". See "Details" for more details of type of simulation.
.postfun
Function applied to the resulting list: list of results from each processed sample.
.verbose
If T than show progress bar.
...
Further values passed to .fun.
Value
Either result from .postfun or list of length .n with values of .fun.
Details
Argument .sim can take two possible values: "uniform" (for uniform distribution), when
each row can be taken with equal probability, and "perccentage" when each row can be taken with
probability equal to its "Percentage" column.
# Apply entropy.seg function to samples of size 20000 from immdata$B data frame for 100 iterations.bootstrap.tcr(immdata[[2]], .fun = entropy.seg, .n = 100, .size = 20000, .sim = 'uniform')