The function subsamples from the rows (observations / cells) in <scores> and uses the subsetted matrix to compute state fractions. This process is repeated <n.iter> times with subsamples of <sample.size>.
bootstrapped_state_fractions(
scores,
sample.size = 200,
n.iter = 10000L,
min = NULL,
diff = NULL,
summary = F
)a dataframe of cell signature scores. Cells are rows and signatures are columns.
the size of the subsample to be taken in each bootstrap. Default: 200
the number of bootstraps or iterations. Default: 10000
minimum value required for a row to be assigned to a column. Default: NULL
minimum difference in value to the 'next-best' row that is required for a row to be assigned to a column. Default: NULL
logical; return summary statistics for bootstraps instead of the raw data. See `?scalop::bootstrap_summary` for details. Default: F
a dataframe with as many columns as <n.iter> and as many rows as the number of columns (signatures) in <scores>. if summary = TRUE, instead returns a dataframe with two columns: mean and SEM.