wrapper around classic process based features

Extracts counts using the default set categories of the process based features, including:

Usage

count_default_process_feats(segs_df, sample_col = "cell_id", with_cn = FALSE)

Arguments

segs_df

dataframe. Segmented CN for samples.

sample_col

string. Column name of sample ID column.

with_cn

bool. default FALSE. FALSE means do not include CN in the feature counts, TRUE will include it.

Details

1. extract_segment_sizes

2. extract_changepoint

3. extract_bp_per_arm

4. extract_bp_per_window

5. extract_oscillations

Not included is CN, which can be added by specifying with_cn=TRUE

Internally using furrr::future_map, so if you set up a future::plan(), this will execute in parallel. Recommended. See Example.

Examples

if (FALSE) { # \dontrun{
future::plan(future::multicore, workers = 10)
dlptools::count_default_process_feats(segs_df, sample_id = "cell_id")
} # }