R/sig_fit_bootstrap_batch.R
sig_fit_bootstrap_batch.Rd
Read sig_fit_bootstrap for more option setting.
sig_fit_bootstrap_batch( catalogue_matrix, methods = c("QP"), n = 100L, min_count = 1L, p_val_thresholds = c(0.05), use_parallel = FALSE, seed = 123456L, job_id = NULL, result_dir = tempdir(), ... )
catalogue_matrix | a numeric matrix |
---|---|
methods | a subset of |
n | the number of bootstrap replicates. |
min_count | minimal exposure in a sample, default is 1. Any patient has total exposure less than this value will be filtered out. |
p_val_thresholds | a vector of relative exposure threshold for calculating p values. |
use_parallel | if |
seed | random seed to reproduce the result. |
job_id | a job ID, default is |
result_dir | see above, default is temp directory defined by R. |
... | other common parameters passing to sig_fit_bootstrap, including
|
a list
of data.table
.
W <- matrix(c(1, 2, 3, 4, 5, 6), ncol = 2) colnames(W) <- c("sig1", "sig2") W <- apply(W, 2, function(x) x / sum(x)) H <- matrix(c(2, 5, 3, 6, 1, 9, 1, 2), ncol = 4) colnames(H) <- paste0("samp", 1:4) V <- W %*% H V if (requireNamespace("quadprog")) { z10 <- sig_fit_bootstrap_batch(V, sig = W, n = 10) z10 }